Compound intake estimator

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Compound intake estimator calculates intakes of compounds based on food or food supplement intake, compound concentration in food, and guidance values for the compound.

Question

How to estimate intakes and compare them to guidance values?

Answer

The concern indicator is calculated for each compound separately. If the intake is smaller than the threshold of concern, the indicator is < 1 and there is no concern. The threshold of concern is acceptable daily indake (ADI), benchmark dose (BMDL10), or threshold of toxicological concern (TTC), depending on what data is available for each compound.

Example data(%)
Obs	Extraction.technique	Compound	Result	Reference
1	Superheated water extraction, 100 °C	2-Carene	0.08; 0.1; 0.12	Jayawardena & Smith, 2010
2	Superheated water extraction, 100 °C	Z-Cinnamaldehyde	1.63; 2.1; 2.57	Jayawardena & Smith, 2010
3	Superheated water extraction, 100 °C	Cinnamaldehyde	81.14; 83.7; 86.26	Jayawardena & Smith, 2010
4	Superheated water extraction, 100 °C	Eugenol	0.45; 0.8; 1.15	Jayawardena & Smith, 2010
5	Hydrodistillation	1,8-Cineole	0.2	Chericoni et al, 2005
6	Superheated water extraction, 100 °C	Cinnamyl acetate	5.47; 7.2; 8.93	Jayawardena & Smith, 2010

Rationale

The idea of the tool is to look at consumption of a particular PFS product, and estimate whether any of the compounds in the product cause concern. The estimation follows this equation:

compound intakes = product intake (g /day) * concentration of each compound in the product (mg /g) / 60
    (60 kg is the assumed body weight of the person)

concern indicator = compound intakes (mg /kg /d) / threshold of concern (mg /kg /d)

Calculations

You need to run the code below only if you update the data tables on this page.

+ Show code - Hide code

library(OpasnetUtils)

################## PRE-DEFINED INPUTS

# food.conc is a temporary object about the concentration of a compound in food.
# compound.conc is the concentration of a compound in the critical constituent (or food, if fr.const == 1) 
# fr.const is the fraction of the critical constituent in the whole food
# extraction is a criteria to select specific extraction techniques
# addcomp is an additional compound not in the product. Data about its concentration in food is given by the user.

# compound.intake is the intakes of the compounds via food or food supplement, each given as mg /kg /d.

compound.intake <- Ovariable("compound.intake", 
	dependencies = data.frame(Names = c(
		"food.amount", 
		"compound.conc", 
		"fr.const", 
		"extraction", 
		"addcomp"
	)), 
	formula = function(...) {
		food.conc <- compound.conc * 10 * fr.const / 100 
		# compound.conc from w/w% to mg/g; fr.const from % to fraction

		food.conc <- food.conc * extraction # remove extractions that are not considered.

		# addcomp  must not contain columns that are not in food.conc. It is multiplied by 1 to make 
		# the result column name "Result".
		food.conc@output <- orbind(food.conc, addcomp * 1)

		test <- colnames(food.conc@output) != "Extraction.technique"
		food.conc@marginal	<- food.conc@marginal[test]
		food.conc@output 	<- food.conc@output[test] # unit: mg /g

		out <- food.amount / 60 * food.conc # scale to 60 kg person
		return(out)
	}
)

# guidance.values is the guidance value (ADI, BMDL10, TTC or similar) for compounds. unit: mg /kg /d
# cramer is cramer classes of compounds (temporary)
# cramer.values are the thresholds of toxicological concern for each Cramer class (temporary)

cramer <- tidy(opbase.data("Op_en6193", subset = "cramer_classes_of_compounds"))
cramer$Result <- NULL
cramer$Guidance <- "TTC" # Threshold for toxicological concern

cramer.values <- tidy(opbase.data("Op_en6193", subset = "cramer_values"))
cramer.values <- merge(cramer, cramer.values)
cramer.values[["Cramer class"]] <- NULL
cramer.values$Result <- cramer.values$Result / 1000 # from ug /kg /d to mg /kg /d

guidance.values <- tidy(opbase.data("Op_en6193", subset = "guidance_values"))
guidance.values <- orbind(cramer.values, guidance.values)
guidance.values <- Ovariable("guidance.values", data = guidance.values)

# food.risk calculates "hazard quotients" or risks relative to guidance values. Value < 1 are of minimal concern

food.risk <- Ovariable(name = "food.risk",
	dependencies = data.frame(Name = c("compound.intake", "guidance.values")),
	formula = function(...) {

		# guidance.risk is intake compared with guidance values.

		out <- compound.intake / guidance.values 

		removepoorguidance <- function(dat, goodg) { # Remove inferior guidance values

			# Compounds that have good guidance values (goodg).
			hasgoodg <- dat[dat$Guidance == goodg , "Compound"] 

			# The row contains data about a chemical with a good guidance value
			# but the data is about an inferior guidance value.

			out <- dat[!(dat$Compound %in% hasgoodg & dat$Guidance != goodg) , ]

			return(out)
		}

		out <- removepoorguidance(out@output, "ADI")
		out <- removepoorguidance(out, "TDI")
		out <- removepoorguidance(out, "BMDL10")

		return(out)
	}
)

extraction <- Ovariable("extraction", ddata = "Op_en6193.extraction_techniques")
extraction@data$extractionResult <- 1

### Define formatting for the concentration graphs that will be shown.

concplot <- function(condition) {
	dat <- compound.conc@output[condition, ]
	if(nrow(dat) != 0) {
		out <- ggplot(dat, 
			aes(
				x = Compound, 
				y = compound.concResult, 
				colour = Extraction.technique
			)) + 
			geom_point(size=5) +
			theme_grey(base_size = 24) +
			theme(axis.text.x = element_text(angle = 90, hjust = 1)) + 
			labs(y = "Concentration (%)")
		return(out)
	} else {
		 warning("No data to show")
	}
}

objects.store(compound.intake, guidance.values, food.risk, extraction, concplot)

cat("The following objects were successfully stored:
compound.intake, guidance.values, food.risk, extraction, concplot\n")

Using different data on different layers: [1].

Extraction techniques

Extraction techniques(-)
Obs	Extraction.technique	Notes
1	Not known
2	Hydrodistillation
3	Solvent extraction
4	Steam distillation
5	Supercritical fluid extraction, 120 bar, 40 °C
6	Supercritical fluid extraction, 90 bar, 40 °C
7	Supercritical fluid extraction, 90 bar, 50 °C
8	Superheated water extraction, 100 °C
9	Superheated water extraction, 150 °C
10	Superheated water extraction, 200 °C
11	Solid phase

Data about guidance values

^[1]

Guidance values(mg /kg-BW /d)
Obs	Compound	Guidance	Result	Notes
1	1,8-Cineole	ADI	2.8
2	4-Terpineol	ADI	1.2
3	Benzylbenzoate	ADI	5
4	Cinnamaldehyde	ADI	0.7
5	Coumarin	TDI	0.1
6	Estragole	BMDL10	3.3-6.5	Data said BMD10 but probably BMDL10
7	Eugenol	ADI	2.5
8	Fenchone	ADI	10.64
9	Limonene	ADI	1
10	Linalool	ADI	0.5
11	Myrcene	ADI	2.5
12	Trans-anethole	ADI	2
13	Safrole	BMDL10	1.9-5.1
14	α-Terpineol	ADI	1.2

Cramer values(µg /kg-BW /d)
Obs	Cramer class	Threshold of toxicological concern	Description
1	1	30
2	2	1.5
3	3	1.5
4	4	0.0025	This comes from Apiole?! Is this correct?

Values 30 and 1.5 µg /kg /d come from EFSA (2012)^[2]

[show]Cramer classes of compounds

Cramer classes of compounds(-)
Obs	Compound	Cramer class	Notes
1	1,8-Cineole	3	A new line was created for 1.8-Cineole based on "ß-Phellandrene + 1,8-Cineole: 1+3"
2	2-Carene	1
3	2-Methoxycinnamaldehyde	1
4	3-Phenylpropyl acetate	1
5	4-Methoxyphenylacetone	1
6	4-Terpineol	3
7	Allo-ocimene	1
8	Apiole	4	This is 0.0025 ug/kg/d!? Is this Cramer class at all?
9	Aromadendrene	1
10	Aromatic compound		Class could not be assigned
11	Benzaldehyde	1
12	Benzenepropanal	1
13	Benzenepropanol acetate	1
14	Benzenepropanol	1
15	Benzylbenzoate	1
16	Borneol	1
17	Cadinene	1
18	Calamenene	2
19	Camphene	1
20	Camphor	3
21	Carvacrol	1
22	Carveol isomere	1	Carveol (2-methyl-5-prop-1-en-2-ylcyclohex-2-en-1-ol) is 1. Isomere is not specified so the class was assigned to the general compound
23	Caryophyllene alcohol	3
24	Caryophyllene oxide	3
25	Caryophyllene	1
26	Chavicol	1
27	Cinnamaldehyde	1
28	Cinnamic acid	1
29	Cinnamyl acetate	1
30	Cinnamyl alcohol	1
31	Cis-anethole	2
32	Cis-limonene oxide	2
33	Cis-P-menth-2-en-1-ol	3
34	Cis-sabinene hydrate	2
35	Cis-ß-Ocimene	1
36	Cis-α-ocimene	1
37	Cis-β-ocimene	1
38	Coumarin	3
39	Cryptone	2
40	Cymene isomere	1	cymene is 1. Isomere is not specified so the class was assigned to the general compound
41	E-Anethole	1
42	e-Cadinene + Pioncarvone		Class could not be assigned
43	E-Cinnamyl acetate	1
44	E-o-Methoxycinnamaldehye	1
45	Epoxy-6.7-Humulene + Mw=220		Class could not be assigned
46	Estragole	1	Test compound, not real value
47	Eugenol acetate	3
48	Eugenol	1
49	Fenchyl acetate	1
50	Humulene epoxide II	3
51	Isoledene	1
52	Limonene	1
53	Linalool	3
54	Methoxy eugenol	3
55	Methyl cinnamaldehyde	1
56	Methyl eugenol	1
57	Monoterpenes		Class could not be assigned
58	N-Hexadecanoic acid	1
59	N-Octadecanoic acid	1
60	o-Cymene	1
61	p-Anisaldehyde	1
62	Para-Methoxy cinnamic aldehyde	1
63	p-Cymene	1
64	P-Cymene-8-ol	3
65	Phenyl cyclohexene	2
66	Phenylmethyle isovalerate	1
67	Rutin	1	Test compound, not real value
68	Sabinene	1
69	Safrole	3
70	Sesquiterpene epoxide		Class could not be assigned. Sesquierpene is class 3, but don't now if something changes with epoxide
71	Sesquiterpenol Mw=220		Class could not be assigned
72	Sesquiterpenol Mw=222		Class could not be assigned
73	Spathulenol	3
74	ß-Bisabolene	1
75	ß-Cubebene	1
76	ß-Elemene	1
77	ß-Myrcene	1
78	ß-Phellandrene	1	ß-Phellandrene + 1,8-Cineole: 1+3
79	ß-Pinene	1
80	Styrene	1
81	Terpinen-4-ol	3
82	Terpinolene isomere	1	terpinolene is 1 , isomere not known. Isomere is not specified so the class was assigned to the general compound
83	Terpinolene	1
84	Tetradecanal	1
85	Trans-2-methoxycinnamaldehyde	1
86	Trans-limonene oxide	2
87	Trans-pinene hydrate	2
88	Trans-Pinocarveol	1
89	Trans-Piperitol	1
90	Trans-P-menth-2-en-1-ol	3
91	Trans-ß-Ocimene	1
92	Z-Cinnamaldehyde	1
93	α-Cadinol	3
94	α-Calacorene	2
95	α-Copaene	1
96	α-Cubebene	1
97	α-Famesene		Class could not be assigned
98	α-Gurjunene	1
99	α-Humulene	1
100	α-Muurolene	1
101	α-Muurolol	3
102	α-P-Dimethylstyrene	1
103	α-Phellandrene	1
104	α-Pinene	1
105	α-Selinene	1
106	α-Terpinene	1
107	α-Terpineol	3
108	α-Thujene	1
109	β-Anise aldehyde	1
110	β-Phellandrene	1
111	β-Pinene	1
112	γ-Cadinene	1
113	γ-terpinene	1
114	γ-Terpinene	1
115	Δ3-Carene	1
116	δ-Cadinene	1

References

↑ New data obtained from Antonella Guzzon, personal communication (email) 31 March 2014.
↑ EFSA (2012). Scientific Opinion on Exploring options for providing advice about possible human health risks based on the concept of Threshold of Toxicological Concern (TTC). EFSA Journal 2012;10(7):2750

[1] New data obtained from Antonella Guzzon, personal communication (email) 31 March 2014.

[EFSA_2012-2] EFSA (2012). Scientific Opinion on Exploring options for providing advice about possible human health risks based on the concept of Threshold of Toxicological Concern (TTC). EFSA Journal 2012;10(7):2750

[1]

[2]