Biology subjects

Isoherranen, N.

Publications and source records attributed to Isoherranen, N..

15 recordsLinked to original sources

bioRxiv2026

Liver Fatty Acid Binding Protein (FABP1) Affects Cytochrome P450 2C9 (CYP2C9)-Mediated Metabolism in Human Liver Models

Metabolic clearance of drugs is often systematically over- or underpredicted from human liver microsomes (HLM). We hypothesized that lack of consideration of interactions of cytosolic liver fatty acid binding protein (FABP1) with drugs and cytochrome P450s (CYPs) explains the off-prediction. We used two CYP2C9 probe substrates, diclofenac and tolbutamide, to test this hypothesis. We found that presence of FABP1 alters the kinetics of metabolite formation in HLM. The model that best fit the kinetic data included FABP1-CYP2C9 protein-protein interactions. Statistical modeling of proteomic expression and drug hydroxylation across a panel of 61 human liver S9 fractions (HLS9) showed that CYP2C9 and FABP1 expression together best predicted probe substrate hydroxylation. Incorporation of FABP1 expression and protein-protein interactions into novel physiologically based liver models significantly improved the quantitative accuracy of in vivo hepatic clearance prediction. Together, our data demonstrate the importance of taking FABP1 into consideration for CYP2C9-mediated metabolism.

pharmacology and toxicology↗

bioRxiv2026

Characterization of Cytochrome P450-Mediated Metabolism of Δ8-tetrahydrocannabinol in vitro

{Delta}-tetrahydrocannabinol ({Delta}8-THC) is a pharmacologically active isomer of {Delta}9-THC, the main psychoactive component of cannabis. {Delta}8-THC use has increased rapidly, but the metabolism of {Delta}8-THC has been incompletely characterized. This study identified metabolites of {Delta}8-THC formed by cytochrome P450 (CYP) enzymes in human liver microsomes (HLM), assigned the main CYPs responsible for the metabolic pathways, and evaluated the impact of genetic polymorphisms on {Delta}8-THC metabolism in vitro. Five monohydroxylated {Delta}8-THC metabolites, identified as 11-OH-{Delta}8-THC, two aliphatic side-chain hydroxylated products (M1, M2), and two ring hydroxylated products (M3, M4) were detected in HLM. 11-OH-{Delta}8-THC was the most abundant metabolite. Unbound binding constants for metabolite formation in HLM ranged from 3.6 nM to >121 nM, suggesting multiple enzymes contribute to {Delta}8-THC metabolism. The contributing enzymes were identified using recombinant CYPs, inhibition studies, and correlation analyses. 11-OH-{Delta}8-THC was predominantly formed by CYP2C9 with a minor contribution from CYP2C19. CYP2C9 genotype-based activity scores across donors correlated with 11-OH-{Delta}8-THC formation (p = 0.0315). An 80% decrease in 11-OH-{Delta}8-THC formation clearance was predicted in CYP2C9*3/*3 carriers. The ring-hydroxylated M3 and M4 were mainly formed by CYP3A. CYP2D6, CYP1A2, and CYP3A4 activities were associated with formation of the pentyl side-chain oxidized metabolites M1 and M2. Although C11 hydroxylation appeared more important metabolic pathway for {Delta}8-THC than for {Delta}9-THC, the catalytic efficiency of CYP2C9 towards {Delta}8-THC was lower than towards {Delta}9-THC. In the presence of CYP2C9 inhibitors or genetic polymorphisms, {Delta}8-THC clearance is likely mediated by CYP3A4 and CYP2C19. This study shows that 11-OH-{Delta}8-THC, a psychoactive metabolite, is the primary oxidation product of {Delta}8-THC in HLM and that CYP2C9 predominantly catalyzes its formation. This work expands the limited literature on {Delta}8-THC metabolism, and shows that reduced-function CYP2C9 variants substantially impair formation of 11-OH-{Delta}8-THC. The characterization of {Delta}8-THC metabolism in HLM provides the foundation for risk assessment of drug-drug interactions and establishes the metabolic profile of {Delta}8-THC in the human liver.

pharmacology and toxicology↗

bioRxiv2026

Proteomic profiling of xenobiotic and nutrient transporters in human placenta of different gestational ages

BackgroundThe placenta serves a critical role in nutrient uptake and waste elimination for the developing fetus. The placenta is also responsible for the uptake and/or exchange of xenobiotics, including medications, between the maternal and fetal bloodstreams. An estimated 40-80% of women take medications or drugs during pregnancy for a variety of conditions. Very little is understood about fetal drug and nutrient exposure during pregnancy and how it may change over the course of fetal development. ObjectiveThis study aimed to characterize the abundance of transport proteins in placental tissue, which are important in modulating fetal nutrient and drug exposure, over the duration of pregnancy. Mass spectrometry-based global proteomic analysis revealed trends in the expression of thousands of proteins throughout gestation. Focusing on the membrane-associated proteome enabled an increased emphasis on the solute carrier and ATP-binding cassette families of transporter proteins that are critical for nutrient and xenobiotic transport across the maternal-fetal barrier. Study DesignUsing data-independent acquisition proteomics, relative abundance of proteins in placental tissue samples was profiled across all three trimesters of pregnancy (Trimester 1 = 16, Trimester 2 = 9, and Term = 9). Membrane fractions were generated to enrich membrane-associated proteins for proteomic analysis. Placental samples were grouped into randomized batches for membrane fraction generation and mass spectrometry analysis. Proteomic search results from each batch were imported into the R programming environment from Skyline, concatenated, and normalized as one data set for downstream analysis. ResultsA total of 6,331 proteins were detected across all samples with 4,210 proteins identified in every sample. Pathway analysis revealed that as gestational age increases, membrane-associated proteins involved in more complex metabolic pathways increase in relative abundance while those involved in extracellular remodeling events and simple organic ion transport tended to decrease. A total of 139 solute carrier and ATP-binding cassette transport proteins were identified in all samples, and 80 were identified in every sample. In general, membrane-associated proteins, including solute carrier and ATP-binding cassette transport proteins, were significantly enriched in placental tissue collected during early gestation compared to term placental tissue. ConclusionThis study presents a comprehensive profiling of membrane-associated proteomic changes during gestation and identifies significant gestational age associated abundance changes at the protein level in several transport protein families. The application of data-independent acquisition global proteomic techniques enabled in-depth analysis of thousands of proteomic changes across pregnancy in a single experiment. These data provide critical information to support future studies into the understanding of fetal exposure to xenobiotics and nutrients circulating in the maternal bloodstream.

pharmacology and toxicology↗

bioRxiv2026

Kinetics of cortisol and cortisone binding to corticosteroid binding globulin and albumin in vivo

Cortisol is a major endogenous glucocorticoid that regulates numerous physiological processes. In plasma, cortisol and its inactive metabolite cortisone bind to corticosteroid-binding globulin (CBG) and albumin, leaving only the unbound fraction available for receptor activation and metabolism. Changes in ligand or protein concentrations alter unbound fractions. Existing binding equations are difficult to extend to multi-ligand, multi-protein systems and do not readily capture competitive endogenous binding interactions. The goal of this study was to develop a plasma protein binding model that quantitatively describes binding species and predicts unbound concentrations across physiological states. Total and unbound cortisol and cortisone, CBG and albumin were measured in plasma from healthy premenopausal women (n=13) at baseline and after 7 days of 30 mg hydrocortisone treatment. Reversible 1:1 binding models were implemented in COPASI and MATLAB/Simulink, and dissociation constants (Kd) were estimated by fitting binding models to observed unbound concentrations. A model describing simultaneous binding of cortisol and cortisone to CBG and albumin yielded in vivo Kd values for cortisol:CBG, cortisone:CBG, cortisol:albumin, and cortisone:albumin of 0.0130 {micro}M, 0.169 {micro}M, 172 {micro}M, and 519 {micro}M, respectively. Model predictions agreed with observed unbound cortisol and cortisone, and bootstrap resampling confirmed stable Kd estimates. This work provides a quantitative framework for predicting unbound cortisol and cortisone across physiological and disease states by accounting for both changes in ligand and protein concentrations. This enables extrapolation without reparameterization and supports exploration of conditions such as pregnancy, adrenal insufficiency, and liver disease, informing interpretation of altered cortisol concentrations in these populations. Significance statementThis work establishes a framework to predict in vivo cortisol and cortisone binding. The developed model was applied to predict unbound cortisol and cortisone concentrations in physiological and pathophysiological states and can be integrated into pharmacokinetic models. Our analysis demonstrates that cortisol and cortisone binding affinities estimated in the native plasma environment differ from those measured using purified proteins. These differences have important implications for predicting and analyzing unbound cortisol concentrations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/718600v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1d9254corg.highwire.dtl.DTLVardef@11fadd5org.highwire.dtl.DTLVardef@cdbc26org.highwire.dtl.DTLVardef@fba0c0_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Authement, A. (2026) https://BioRender.com/zl1bg0k

pharmacology and toxicology↗

bioRxiv2026

Development of Physiologically Based Liver Distribution Model that Incorporates Intracellular Lipid Partitioning and Binding to Fatty Acid Binding Protein 1 (FABP1)

Steady-state volume of distribution (Vss) can be predicted using tissue-to-plasma partition coefficients (Kp) and tissue volumes. Kp values are important components of physiologically based pharmacokinetic (PBPK) models, allowing for estimation of distribution kinetics and simulation of concentration-time profiles. Many in silico approaches have been developed to predict tissue Kp values based on physicochemical processes that govern drug distribution. However, these methods frequently over- or under-predict tissue Kp values, highlighting the need to consider additional mechanisms that can impact drug distribution kinetics. Many drugs have been shown to bind to rat and human fatty acid binding proteins (FABPs) in vitro but the impact of this binding to drug distribution has not been incorporated into Kp predictions. We hypothesized that incorporating intracellular protein binding into tissue Kp predictions will improve Kp prediction accuracy. Using liver as a model organ, four physiologically based dynamic liver distribution models (LDMs) were developed to assess the role of distribution processes in Kp predictions. The developed LDMs incorporated known distribution mechanisms and intracellular drug binding to liver FABP (FABP1). The liver Kp values for drugs that bind to FABP1 were accurately predicted using the LDM that incorporates lipid partitioning, albumin distribution, and FABP1 binding but not using LDMs without FABP1 binding. Human FABP1 expression was quantified in 61 human livers and the interindividual variability in tissue FABP1 binding was incorporated into tissue Kp predictions. These simulations showed that intracellular FABP1 binding can cause interindividual variability in Kp values and result in concentration dependent tissue distribution. Significance StatementThis study shows that incorporating intracellular protein binding such as binding to FABP1 into tissue Kp predictions improves accuracy of the predictions. The novel dynamic LDM can be extrapolated to other organs of interest and integrated into full-body PBPK models to predict drug distribution kinetics. With dynamic and saturable distribution mechanisms incorporated into a PBPK model, nonlinear distribution kinetics can be simulated for various drugs.

pharmacology and toxicology↗

bioRxiv2026

Proteomic Profiling of Human Omental and Subcutaneous Adipose Tissue in Individuals with a Broad Range of BMI.

Obesity is a major public health challenge affecting an ever-increasing proportion of the global population. It is associated with numerous comorbidities. Progressive expansion and remodeling of adipose tissue may lead to depot specific changes in adipose tissue biology and energy partitioning. Such changes likely precede the development of obesity-related complications. To facilitate a deeper understanding of adipose tissue biology, a comprehensive and quantitative proteomic dataset at the peptide and protein level is presented. Data-independent acquisition LC-MS/MS data were acquired from matched subcutaneous and omental adipose tissues from metabolically healthy individuals with no comorbidities and covering a wide range of body mass indexes. Adipose tissue samples were collected during elective surgeries and immediately processed for histology or frozen until proteomic analysis. Internal and external quality control systems ensured high quality data. All data presented are available via ProteomeXchange. This dataset will allow new insights into biological changes that evolve with increasing adiposity captured before the onset of comorbidities. Matched sampling across fat depots provides an opportunity to uncover depot-specific physiological signatures.

systems biology↗

bioRxiv2025

Dicloxacillin and flucloxacillin inhibit hepatic uptake transporters - in vitro investigations and physiological based pharmacokinetic modelling

Dicloxacillin and flucloxacillin are {beta}-lactamase-resistant penicillin antibiotics that have been in clinical use for over 50 years. While both antibiotics are known to induce cytochrome P450 enzymes, there is limited information available regarding their interactions with drug transporters. Here, we investigated the in vitro transport and inhibition of hepatic organic anion transporting polypeptides (OATPs) and renal organic anion transporters (OATs) by these antibiotics in recombinant transporter overexpressing HEK293 cells. We also investigated the transport of these antibiotics by efflux transporters, as well as their inhibition of breast cancer resistance protein (BCRP) and P-glycoprotein (P-gp) using a HEK293 membrane vesicle transport assay. Dicloxacillin and flucloxacillin inhibited rosuvastatin transport by OATP1B1, OATP1B3 and OATP2B1, and the inhibition was strongest for OATP1Bs with IC50 values of 3.9 {micro}M and 31 {micro}M (OATP1B1) and 6.7 {micro}M and 21 {micro}M (OATP1B3) for dicloxacillin and flucloxacillin, respectively. Both antibiotics also inhibited BCRP-mediated rosuvastatin transport with IC50 values of 166 {micro}M (dicloxacillin) and 379 {micro}M (flucloxacillin), while P-gp-mediated transport of N-methyl-quinidine was inhibited to a lesser extent. All OATPs and OATs transported dicloxacillin and flucloxacillin. Static model predictions indicated that the inhibition of OATPs, BCRP and P-glycoprotein by both compounds may be clinically relevant. We further developed and verified physiologically based pharmacokinetic (PBPK) models for dicloxacillin and flucloxacillin. PBPK model simulations predicted no major change in rosuvastatin, a substrate for OATPs and BCRP, pharmacokinetics, when co-administered with dicloxacillin or flucloxacillin. Simulations with dicloxacillin and P-gp substrates dabigatran or digoxin also predicted limited inhibition of P-gp transport.

pharmacology and toxicology↗

bioRxiv2025

Development and Validation of a Novel LC-MS/MS Based Proteomics Method for Quantitation of Retinol Binding Protein 4 (RBP4) and Transthyretin (TTR)

Retinol binding protein 4 (RBP4), the circulating carrier of retinol, complexes with transthyretin (TTR) and is a potential biomarker of cardiometabolic disease. However, RBP4 quantitation relies on immunoassays and western blots without retinol and TTR measurement. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous absolute quantitation of circulating RBP4 and TTR is critical to establishing their biomarker potential. Surrogate peptides with reproducible, linear LC-MS/MS response were selected. Purified proteins were used as quantitation standards and heavy-labelled peptides as internal standards. Matrix effects were evaluated. The validated method was applied to measure inter- and intra-individual variability in RBP4 and TTR concentrations in healthy individuals and patients with diabetic kidney disease. Quantitation was linear for the clinically relevant concentration ranges of RBP4 (0.5-6 {micro}M) and TTR (5.8-69 {micro}M). Assay inter-day variability was <12% and precision within 5%. The inter-individual variability for RBP4 and TTR concentrations was 18-26%, while intra-individual variability was similar to assay variability. RBP4 and TTR quantitation correlated with commercially available ELISA assays. The developed LC-MS/MS method enables simultaneous absolute quantitation of RBP4 and TTR in serum and plasma that can be applied to clinical biomarker studies and stoichiometric measurements of circulating RBP4, TTR, and retinol.

physiology↗

bioRxiv2024

Limelight - An open, web-based tool for visualizing, sharing, and analyzing mass spectrometry data from DDA pipelines

Liquid chromatography-tandem mass spectrometry employing data-dependent acquisition (DDA) is a mature, widely used proteomics technique routinely applied to proteome profiling, protein-protein interaction studies, biomarker discovery, and protein modification analysis. Numerous tools exist for searching DDA data and myriad file formats are output as results. While some search and post processing tools include data visualization features to aid biological interpretation, they are often limited or tied to specific software pipelines. This restricts the accessibility, sharing and interpretation of data, and hinders comparison of results between different software pipelines. We developed Limelight, an easy-to-use, open-source, freely available tool that provides data sharing, analysis and visualization and is not tied to any specific software pipeline. Limelight is a data visualization tool specifically designed to provide access to the whole "data stack", from raw and annotated scan data to peptide-spectrum matches, quality control, peptides, proteins, and modifications. Limelight is designed from the ground up for sharing and collaboration and to support data from any DDA workflow. We provide tools to import data from many widely used open-mass and closed-mass search software workflows. Limelight helps maximize the utility of data by providing an easy-to-use interface for finding and interpreting data, all using the native scores from respective workflows.

bioinformatics↗

bioRxiv2024

Drugs Form Ternary Complexes with Human Liver Fatty Acid Binding Protein (FABP1) and FABP1 Binding Alters Drug Metabolism

Liver fatty acid binding protein (FABP1) binds diverse endogenous lipids and is highly expressed in the human liver. Binding to FABP1 alters the metabolism and homeostasis of endogenous lipids in the liver. Drugs have also been shown to bind to rat FABP1, but limited data is available for human FABP1 (hFABP1). FABP1 has a large binding pocket and multiple fatty acids can bind to FABP1 simultaneously. We hypothesized that drug binding to hFABP1 results in formation of ternary complexes and that FABP1 binding alters drug metabolism. To test these hypotheses native protein mass spectrometry (MS) and fluorescent 11-(dansylamino)undecanoic acid (DAUDA) displacement assays were used to characterize drug binding to hFABP1 and diclofenac oxidation by cytochrome P450 2C9 (CYP2C9) was studied in the presence and absence of hFABP1. DAUDA binding to hFABP1 involved high (Kd,1=0.2 {micro}M) and low affinity (Kd,2 >10 {micro}M) binding sites. Nine drugs bound to hFABP1 with Kd values ranging from 1 to 20 {micro}M. None of the tested drugs completely displaced DAUDA from hFABP1 and fluorescence spectra showed evidence of ternary complex formation. Formation of DAUDA-diclofenac-hFABP1 ternary complex was verified with native MS. Docking placed diclofenac in the portal region of FABP1 with DAUDA in the binding cavity. Presence of hFABP1 decreased the kcat and Km,u of diclofenac with CYP2C9 by [~]50% suggesting that hFABP1 binding in the liver will alter drug metabolism and clearance. Together, these results suggest that drugs form ternary complexes with hFABP1 and that hFABP1 interacts with CYP2C9. Significance statementMany commonly prescribed drugs bind FABP1 forming ternary complexes with FABP1 and the fluorescent fatty acid DAUDA. This suggests that in the human liver drugs will bind to apo-FABP1 and fatty acid bound FABP1. The high expression of FABP1 in the liver and binding of drugs to FABP1 will alter rates of drug metabolism in the liver.

pharmacology and toxicology↗

bioRxiv2021

Discovery and visualization of uncharacterized drug-protein adducts using mass spectrometry.

Drugs are often metabolized to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life threatening adverse drug reactions. The masses of reactive metabolites are frequently unknown, rendering traditional mass spectrometry-based proteomics incapable of adduct identification. Here, we present Magnum, an open-mass search algorithm optimized for adduct identification, and Limelight, a web-based data processing package for analysis and visualization of data from all existing algorithms. Limelight incorporates tools for sample comparisons and xenobiotic-adduct discovery. We validate our tools with two drug/protein combinations and apply our workflow to identify novel xenobiotic-protein adducts in CYP3A4. Our new methods and software enable accurate identification of xenobiotic-protein adducts with no prior knowledge of adduct masses or protein targets. Magnum outperforms existing tools in xenobiotic-protein adduct discovery, while Limelight fulfills a major need in the rapidly developing field of open-mass searching, which until now lacked comprehensive data visualization tools.

pharmacology and toxicology↗

bioRxiv2020

Bridging the gap between in silico and in vivo: modeling opioid disposition in a kidney proximal tubule microphysiological system

BackgroundOpioid overdose, dependence, and addiction are a major public health crisis. Patients with chronic kidney disease (CKD) are at high risk of opioid overdose, therefore novel methods that provide accurate prediction of kidney clearance (CLr) and systemic disposition of opioids in CKD patients can facilitate the optimization of therapeutic regimens. MethodsWe conducted prediction of kidney clearance and systemic disposition of morphine and its active metabolite morphine-6-glucuronide (M6G) in CKD patients using a vascularized human proximal tubule microphysiological system (VPT-MPS) coupled with a parent-metabolite full body physiologically-based pharmacokinetic (PBPK) model. ResultsThe VPT-MPS, populated with a human umbilical vein endothelial cell (HUVEC) channel and an adjacent human primary proximal tubular epithelial cells (PTEC) channel, successfully demonstrated secretory transport of morphine and M6G from the HUVEC channel into the PTEC channel in a time-dependent manner; transporter inhibitors decreased translocation by 74.3% and 63.6%, respectively. The in vitro data generated by VPT-MPS were incorporated into a mechanistic kidney model and parent-metabolite full body PBPK model to predict CLr and systemic disposition of morphine and M6G. The model successfully predicted CLr within 1.5-fold, and the plasma concentration-time profiles of morphine and M6G in both healthy subjects and CKD patients, with absolute average fold error values <1.5. ConclusionsA microphysiological system together with mathematical modeling successfully predicted kidney clearance and systemic disposition of opioids in CKD patients and healthy subjects.

pharmacology and toxicology↗

bioRxiv2020

In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N=80 samples from persons with RT-PCR confirmed SARS-CoV2 infection), and a specificity of 97.2% (N=106 control samples).

bioinformatics↗

bioRxiv2018

Preclinical Modeling of Exposure to a Global Marine Bio Contaminant: Effects of In Utero Domoic Acid Exposure on Neonatal Behavior and Infant Memory

Domoic Acid (DA) is a naturally-occurring marine neurotoxin that is increasingly recognized as an important public health issue. Prenatal DA exposure occurs through the maternal consumption of contaminated shellfish/finfish. To better understand the fetal risks associated with DA, we initiated a longitudinal, preclinical study focused on the reproductive and developmental effects of chronic, low-dose oral DA exposure. To this end, 32 adult female Macaca fascicularis monkeys were orally dosed with 0, 0.075 or 0.15 mg/kg/day DA on a daily basis prior to breeding and throughout breeding and pregnancy. The doses included the proposed human Tolerable Daily Intake (TDI) (0.075 mg/kg/day) for DA. Adult females were bred to nonexposed males. To evaluate development during early infancy, offspring were administered a Neonatal Assessment modeled after the human Neonatal Behavior Assessment Scale and a series of Visual Recognition Memory problems using the novelty paradigm. Results indicated that prenatal DA exposure did not impact early survival reflexes or responsivity to the environment. Findings from the recognition memory assessment, given between 1-2 months of age, showed that exposed and control infants demonstrated robust novelty scores when test problems were relatively easy to solve. Performance was not diminished by the introduction of delay periods. However, when more difficult recognition problems were introduced, the looking behavior of the 0.15 mg/kg DA group was random and infants failed to show differential visual attention to novel test stimuli. This finding suggests subtle but significant impairment in recognition memory and demonstrates that chronic fetal exposure to DA may impact developing cognitive processes.

pharmacology and toxicology↗

bioRxiv2018

Effects of Oral Domoic Acid Exposure on Maternal Reproduction and Infant Birth Characteristics in a Preclinical Nonhuman Primate Model

Domoic Acid (DA) is a naturally-occurring excitotoxin, produced by marine algae, which can bioaccumulate in shellfish and finfish. The consumption of seafood contaminated with DA is associated with gastrointestinal illness that, in the case of high DA exposure, can evolve into a spectrum of responses ranging from agitation to hallucinations, memory loss, seizures and coma. Because algal blooms that produce DA are becoming more widespread and very little is known about the dangers of chronic, low-dose exposure, we initiated a preclinical study focused on the reproductive and developmental effects of DA in a nonhuman primate model. To this end, 32 adult female Macaca fascicularis monkeys were orally exposed to 0, 0.075 or 0.15 mg/kg/day DA on a daily basis, prior to and during pregnancy. Females were bred to non-exposed males and infants were evaluated at birth. Results from this study provided no evidence of changes in DA plasma concentrations with chronic exposure. DA exposure was not associated with reproductive toxicity or adverse changes in the physical characteristics of newborns. However, in an unanticipated finding, our clinical observations battery revealed the presence of subtle neurological effects in the form of intentional tremors in the exposed adult females. While females in both dose groups displayed increased tremoring, the effect was dose-dependent and observed at a higher frequency in females exposed to 0.15 mg/kg/day. These results demonstrate that chronic, low-level exposure to DA is associated with injury to the adult CNS and suggest that current regulatory guidelines designed to protect human health may not be adequate for high-frequency shellfish consumers.\n\nHighlights1) Domoic acid acts as a tremoragen after chronic, low-dose oral exposure in adults.\n\n2) Exposure across pregnancy does not result in maternal reproductive toxicity.\n\n3) In-utero exposure does not adversely impact physical characteristics of exposed newborns.\n\n4) Current regulatory guidelines may not adequately protect high-frequency shellfish consumers from DA-induced neurological injury.

pharmacology and toxicology↗