Fred Parham

Neurite outgrowth in human induced pluripotent stem cell-derived neurons as a high-throughput screen for developmental neurotoxicity or neurotoxicity

Due to the increasing prevalence of neurological disorders and the large number of untested compounds in the environment, there is a need to develop reliable and efficient screening tools to identify environmental chemicals that could potentially affect neurological development. Herein, we report on a library of 80 compounds screened for their ability to inhibit neurite outgrowth, a process by which compounds may elicit developmental neurotoxicity, in a high-throughput, high-content assay using human neurons derived from induced pluripotent stem cells (iPSC). The library contains a diverse set of compounds including those that have been known to be associated with developmental neurotoxicity (DNT) and/or neurotoxicity (NT), environmental compounds with unknown neurotoxic potential (e.g., polycyclic aromatic hydrocarbons (PAHs) and flame retardants (FRs)), as well as compounds with no documented neurotoxic potential. Neurons were treated for 72h across a 6-point concentration range (∼0.3-100μM) in 384-well plates. Effects on neurite outgrowth were assessed by quantifying total outgrowth, branches, and processes. We also assessed the number ofviable cells per well. Concentration-response profiles were evaluated using a Hill model to derive benchmark concentration (BMC) values. Assay performance was evaluated using positive and negative controls and test replicates. Compounds were ranked by activity and selectivity (i.e., specific effects on neurite outgrowth in the absence of concomitant cytotoxicity) and repeat studies were conducted to confirm selectivity. Among the 80 compounds tested, 38 compounds were active, of which 16 selectively inhibited neurite outgrowth. Of these 16 compounds, 12 were known to cause DNT/NT and the remaining 4 compounds included 3 PAHs and 1 FR. In independent repeat studies, 14/16 selective compounds were reproducibly active in the assay, of which only 6 were selective for inhibition of neurite outgrowth. These 6 compounds were previously shown in the literature to be neurotoxic. These studies shed light on the current status of human iPSCs in DNT/NT screening and their utility in identifying, ranking, and prioritizing compounds with DNT/NT potential for further in vivo testing.

Upstream adverse effects in risk assessment: A model of polychlorinated biphenyls, thyroid hormone disruption and neurological outcomes in humans

BACKGROUND Increasing data on early biological changes from chemical exposures requires new interpretation tools to support decision-making. OBJECTIVES To test the possibility of applying a quantitative approach using human data linking chemical exposures and upstream biological perturbations to overt downstream outcomes. METHODS Using polychlorinated biphenyl (PCB) exposures and maternal thyroid hormone (TH) perturbations as a case study, we model three relationships: (1) prenatal PCB exposures and TH changes, using free T(4) (FT(4)); (2) prenatal TH and childhood neurodevelopmental outcomes; and (3) prenatal PCB exposures and childhood neurodevelopmental outcomes (IQ). We surveyed the epidemiological literature; extracted relevant quantitative data; and developed models for each relationship, applying meta-analysis where appropriate. RESULTS For relationship 1, a meta-analysis of 3 studies gives a coefficient of -0.27 pg/mL FT(4) per ln(sum of PCBs) (95% confidence interval [CI] -0.82 to 0.27). For relationship 2, regression coefficients from three studies of maternal FT(4) levels and cognitive scores ranged between 0.99 IQ points/(pg/mL FT(4)) (95% CI -0.31 to 2.2) and 7.6 points/(pg/mL FT(4)) (95% CI 1.2 to 16.3). For relationship 3, a meta-analysis of five studies produces a coefficient of -1.98 IQ points (95% CI -4.46 to 0.50) per unit increase in ln(sum of PCBs). Combining relationships 1 and 2 yields an estimate of -2.0 to -0.27 points of IQ per unit increase in ln(sum of PCBs). CONCLUSIONS Combining analysis of chemical exposures and early biological perturbations (PCBs and FT(4)) with analysis of early biological perturbations and downstream overt effects (FT(4) and IQ) yields estimates within the range of studies of exposures and overt effects (PCBs and IQ). This is an example approach using upstream biological perturbations for effect prediction.

Dose-Response Modeling of High-Throughput Screening Data

The National Toxicology Program is developing a high-throughput screening (HTS) program to set testing priorities for compounds of interest, to identify mechanisms of action, and potentially to develop predictive models for human toxicity. This program will generate extensive data on the activity of large numbers of chemicals in a wide variety of biochemical- and cell-based assays. The first step in relating patterns of response among batteries of HTS assays to in vivo toxicity is to distinguish between positive and negative compounds in individual assays. Here, the authors report on a statistical approach developed to identify compounds positive or negative in an HTS cytotoxicity assay based on data collected from screening 1353 compounds for concentration-response effects in 9 human and 4 rodent cell types. In this approach, the authors develop methods to normalize the data (removing bias due to the location of the compound on the 1536-well plates used in the assay) and to analyze for concentration-response relationships. Various statistical tests for identifying significant concentration-response relationships and for addressing reproducibility are developed and presented.

Adverse effects in risk assessment: Modeling polychlorinated biphenyls and thyroid hormone disruption outcomes in animals and humans

There is a growing need for quantitative approaches to extrapolate relationships between chemical exposures and early biological perturbations from animals to humans given increasing use of biological assays to evaluate toxicity pathways. We have developed such an approach using polychlorinated biphenyls (PCBs) and thyroid hormone (TH) disruption as a case study. We reviewed and identified experimental animal literature from which we developed a low-dose, linear model of PCB body burdens and decrements in free thyroxine (FT(4)) and total thyroxine (TT(4)), accounting for 33 PCB congeners; extrapolated the dose-response from animals to humans; and compared the animal dose-response to the dose-response of PCB body burdens and TH changes from eleven human epidemiological studies. We estimated a range of potencies for PCB congeners (over 4 orders of magnitude), with the strongest for PCB 126. Our approach to developing toxic equivalency models produced relative potencies similar to the toxicity equivalency factors (TEFs) from the World Health Organization (WHO). We generally found that the dose-response extrapolated from the animal studies tends to under-predict the dose-response estimated from human epidemiological studies. A quantitative approach to evaluating the relationship between chemical exposures and TH perturbations, based on animal data can be used to assess human health consequences of thyroid toxicity and inform decision-making.

The Use of signal-Transduction and Metabolic Pathways to Predict human Disease Targets from electric and Magnetic Fields Using in vitro Data in human cell lines

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK–STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders.

Importance of CDK7 for G1 Re-Entry into the Mammalian Cell Cycle and Identification of New Downstream Networks Using a Computational Method

Many of the key molecules in cell cycle progression (e.g. pRB, cyclin complexes) and their basic interactions are oncogene or tumor suppressor genes, which are well characterized in the clinical and experimental analysis. However, there are still unknown mechanisms for the cell cycle regulation, which is critical step for the progression of the cancer development. Especially it is not fully understood how the cells move to G1 phase from quiescent G0 phase in the mammalian cells. To find out the new gene networks associated with the two transition of the mammalian cell cycle (G0 to G1 and G1 to S phase), we analyzed the linkages between 39 representative oncogene or tumor suppressor genes, which related to the cell cycle regulation, with gene expression sets obtained from the publicly opened microarray data for mouse embryonic fibroblasts that synchronized by the serum starvation or hydroxyurea treatment. Analyses with a qualitative algorithm based on Bayesian networks that assume a log-linear relationship between genes have applied, and newly found networks were validated. Results highlighted the importance of two master genes, Cdk7 and Cdkna2 for the re-entry to G1 from G0, and suggested a new network connection from Cdk7 to downstream molecules, including the EGF receptor and N-myc. Introduction of a recombinant Cdk7 with retrovirus decreased endogenous EGFR and N-myc protein levels. The results supported the computational prediction of the Cdk7 network. Taken together, these result showed the existence of new regulating pathway from Cdk7 to Egfr and N-myc, suggesting this analytical approach provides an assessment of regulatory networks in complex mammalian cells, and the process of the carcinogenesis.