Food Toxicology Learning Objectives • Understand the quantitative relationship between toxicant exposure and induced effects. • Describe frequently encountered toxic effects. Dose - Response Relationships • Interpret frequency (normal distribution) and dose - response curves. • Understand threshold Food Toxicology effects with dosage Instructor: Gregory Möller, Ph.D. increase. University of Idaho

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Food Toxicology Food Toxicology Learning Objectives, 2 What is a Dose? • Understand effective dose, margin-of-safety and • The amount of a substance administered at the relationship of effective vs. toxic dose. one time. • Examine the use of actual data for no observed • Dosage is the amount per unit weight of the effect and lowest observed exposed individual. effect in risk assessments. • Exposure is characterized • Summarize effective, lethal by and toxic doses. – Number of doses • Understand a linearized – Frequency of dosing multi-stage model for – The total period of time non-threshold responses. for the exposure.

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Food Toxicology Food Toxicology Quantifying the Dose Key Concepts • Gram (g) is the standard unit but mg is typical • Dosage - response mathematical relationship of most exposures in toxicology. (positive slope). • Dosage: mg (dose) / kg (bw) / day (duration) • Causal relationship. –mg/kg/d • Observable responses. • Exposures are quantified in relation to the • Statistical management of variability media. of individual responses. – mg/L in water. – mg/kg in food. – Species, genetics, age, sex. –mg/m3 in air. • Variation in units common (ppm, ppb).

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•1 Food Toxicology Food Toxicology Responses (Toxic Effects) Responses (Toxic Effects), 2 • Inflammation. • Lethal synthesis. – Local or systemic response. – Toxicant incorporation into a biochemical pathway. • Necrosis. • Lipid peroxidation. – Cell or tissue death. – Free radical oxidation of fatty acids leading to cell death. • Enzyme inhibition. • Covalent binding. – Biochemical pathway interruption. – Of electrophilic reactive – Competitive; non-competitive. metabolites to nucleophillic • Biochemical uncoupling. macromolecules. – Interference with phosphate molecule synthesis (ATP)

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Food Toxicology Food Toxicology Responses (Toxic Effects), 3 Responses (Toxic Effects), 4 • Receptor interaction. • Neoplasia. – Modification of normal biological effects mediated – Aberrant cell division and tissue growth. by the receptor. • Neoplasms: tumorigenesis, oncogenesis. • Immune-mediated hypersensitivity reactions. • Malignant neoplasms: carcinogenesis. – Antigenic chemicals resulting in allergic reaction. • Immuno-suppression. – Increased susceptibility to infectious agents and tumorigenesis.

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Food Toxicology Food Toxicology Responses (Toxic Effects), 5 Types of Toxic Responses: Idiosyncratic • Genotoxic interaction. • Genetically determined sensitivity or resistance to – Chemical interaction with DNA possibly leading to toxicity heritable change. – Usually lack of enzymes / factor involved in metabolism • Clastogenic (chromosomal) effects. • Primaquine (oxidative anti-malarial drug) - 10% • Mutagenic (base pair) effects. black males / erythrocyte G-6-P dehydrogenase / hemolytic anemia • Developmental and reproductive toxicity. – Glucose-6-phosphate – Adverse effects on dehydrogenase deficiency, conception, and the most common enzyme structure and function deficiency worldwide of the conceptus. • Nitrites - lack NADH-methemoglobin reductase / methemoglobinemia 11 12

•2 Food Toxicology Food Toxicology Types of Toxic Responses: Allergic Dose-Response • Immunological mediated response (memory) • Quantitative analysis of incremental dose increase • Requires sensitizing exposure and occurrence of toxic end effect • May involve chemical/protein complex (hapten) • Responses follow normal frequency distribution • Atypical dose response (gaussian) – Small doses most effective – Large dose tolerance • Ts cells (suppressor T lymphocytes) • Contact dermatitis; anaphylaxis • Pollens, pesticides, sulfur, penicillin 13 14

Food Toxicology Food Toxicology Normal (Gaussian) Distribution Normal Distribution, 2

• Population representation of variability.

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Food Toxicology Food Toxicology Normal Distribution Parameters Dose - Response Curve • Mean + one SD = 68.3 % population Resistant • Mean + two SD = 95.5 % population • Mean + three SD = 99.7 % population

• Frequency converted to cumulative gives sigmoid curve Sensitive

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•3 Food Toxicology Food Toxicology Observed Effects Toxic Thresholds

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Food Toxicology Food Toxicology

Median Lethal Dose LD50 Shape and Slope Interpretation • Often used to compare toxicity • Only measures lethality • Best for quantal data • Best for acute exposure • Tells nothing about slope • Specific quantifiers

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Food Toxicology Food Toxicology

Comparative Toxicity Other Thresholds: ED90 – EC50 – LC10 – TDLo • ED: effective dose – Pharmaceuticals • EC: effective concentration – Pharmaceuticals in vivo • Often blood – Environmental toxicology • LC: lethal concentration – Environmental toxicology

•TDLo: Lowest published toxic dose

•TCLo: Lowest published toxic concentration

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•4 Food Toxicology Food Toxicology Therapeutic Index - TI Effective Dose • Ratio of dose to produce toxic effect to dose to produce desired effect

•TI = LD50/ED50 • The larger the ratio, the greater the safety (e.g. 10) • Slope of dose response important

Therapeutic Index (TI) = Toxic Dose/Therapeutic Dose

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Food Toxicology Food Toxicology Margin of Safety Margin of Safety - MOS • Accounts more for slope differences

• MOS = LD1/ED99 • Neither TI or MOS works for chemicals with no beneficial effect or repeated doses

Margin of Safety (MOS) = LD(01)/ED(99) 27 28

Food Toxicology Food Toxicology Carcinogen Risk Assessment Linearized Multistage Model • Linearized Multistage Model – Assumes non-threshold effect. • Linear extrapolation through zero threshold dose from upper confidence level of lowest dose that caused cancer in animal study. • Analysis results in a cancer slope factor that can be used to predict cancer risk at a specific dose.

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•5 Food Toxicology Food Toxicology Other Models for Risk Assessment Transformation of Variables • One hit model (cancer) • Allows better (simpler) analysis of data at points of interest – Assumes a molecular event with cellular response. such as LD50. • Multi hit model (cancer) • Transformation into an approximate normally distributed variable. – Assumes multiple events prior to cellular activation. •Examples (rj = dead animals; nj = total animals) • Probit model • Probit transformation. – Linearization transformation that – Based on Gaussian (Bell) curve. -1 assumes log normal distribution. – Probit (rj/nj) = Φ (rj/nj) – Useful in acute lethality tests. • PB PK - Physiologically based • Logit transformation. pharmacokinetic model – Log odds of a quantal response.

– Uses intensive pharmacokinetic – Logit (rj/nj) = ln [(rj/nj)/1 - (rj/nj)] and mechanistic data. • Weibull transformation. – Exponential model used in modeling multistage processes. 31 32

Food Toxicology Food Toxicology Probit Transformation Probit Transformation, 2 • Probability units → “probits” % Response SD NED Probit • Convert % response to units of deviation from the 0.1 -3 -3 2 mean or “normal equivalent deviations” (NEDs). 2.3 -2 -2 3 • Hence the NED for a 50% response is 0. 15.9 -1 -1 4 • “Probit” approach adds 5 50.0 mean 0 5 to avoid negatives. 84.1 +1 +1 6 97.7 +2 +2 7 99.9 +3 +3 8

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Food Toxicology Food Toxicology Probit Transformation, 3 Log Normal Distribution

• Perform log10 transformation of the dose. – Assumes log normal distribution. • Produces an approximately linear relationship. – Allows linear regression analysis.

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•6 Food Toxicology Food Toxicology Probit Unit Transformation Summary: Transformations of D-R Curve • Normal frequency distribution • Arithmetic dose to log dose • Frequency data to cumulative • Probability of response to NED – Standard deviations of mean • NED to probit –NED + 5

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Food Toxicology Dose-Response Curve Summary Major Parameters

• Median Lethal Dose - LD50 – Other LDs, TDs or EDs • Slope • Thresholds • System saturations • Comparative toxicity • Risk assessment

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