III. Celiac Disease
B. Mechanism of Pathogenesis
Figure III-1. Mechanism of Celiac Disease
C. Range of Adverse Effects
The clinical manifestations of celiac disease are highly variable in character and severity. The reasons for this diversity are unknown but may depend on the age and immunological status of the individual, the amount, duration, or timing of exposure to gluten, and the specific area and extent of the gastrointestinal tract involved by disease (Dewar et al., 2004). These clinical manifestations can be divided into gastrointestinal, or "classic," and non-gastrointestinal manifestations. Gastrointestinal manifestations usually present in children 4 to 24 months old and include abdominal pain and cramping, bloating, recurrent or chronic diarrhea in association with weight loss, poor growth, nutrient deficiency, and (in rare cases) a life-threatening metabolic emergency termed celiac crisis, characterized by hypokalemia and acidosis secondary to profuse diarrhea (Farrell and Kelly, 2002; Baranwal et al., 2003). Non-gastrointestinal manifestations are more insidious and highly variable and are the common presenting signs in older children and adults. These manifestations are frequently the result of long-term nutrient malabsorption, including iron deficiency anemia, short stature, delayed puberty, infertility, and osteoporosis or osteopenia (Fasano, 2003). In children, progressive malabsorption of nutrients may lead to growth, developmental, or neurological delays (Catassi and Fasano, 2004). Extra-intestinal manifestations such as dermatitis herpetiformis, hepatitis, peripheral neuropathy, ataxia, and epilepsy have also been associated with celiac disease (Fasano and Catassi, 2001). Individuals with untreated celiac disease are also at increased risk for potentially serious medical conditions, such as other autoimmune diseases (e.g., Type I diabetes mellitus) and intestinal cancers associated with high mortality (Farrell and Kelly, 2002; Peters et al., 2003; Catassi et al., 2002). For example, individuals with celiac disease have an 80-fold greater risk of developing adenocarcinoma of the small intestine, a greater than two-fold increased risk for intestinal or extraintestinal lymphomas (Green and Jabri, 2003) and a 20-fold greater risk of developing enteropathy-associated T cell lymphoma (EATL) (Catassi et al., 2005a). These are rare intestinal malignancies with a high mortality rate. In addition, the relative risk for developing non-Hodgkin's lymphomas, intestinal or extraintestinal, is three fold greater than in the general population (Catassi et al., 2002). These cancers contribute to nearly two thirds of deaths due to celiac disease and are a major reason for the nearly two-fold increase in overall mortality of adult patients with celiac disease compared to the general population (Corrao et al., 2001).
Currently, individuals with clinical manifestations, or "symptomatic" celiac disease, are believed to represent a small portion of the total affected population (Mäki and Collin, 1997). A larger number of individuals are believed to have "silent" celiac disease, characterized by positive serology and intestinal mucosal abnormalities in the absence of symptoms or nutritional deficiencies. Mäki and Collin (1997) also suggested that there is an even larger population with "latent" celiac disease, individuals who are positive for serological markers or genetic susceptibility to disease and are entirely asymptomatic. It is generally accepted that individuals with silent or latent disease, although asymptomatic, have the capability to manifest aberrant immune responses following exposure to dietary glutens and are, therefore, at increased risk for both acute and long-term complications of celiac disease (Fasano, 2003; Schuppan, 2000). However, the long-term benefit of strict gluten avoidance for these individuals is unproven (Green and Jabri, 2003).
Until recently, celiac disease was considered to be a rare disorder in the U.S., with an estimated prevalence rate of 1:5,000 (Talley, 1994). However, a large epidemiological study screened more than 13,000 people in 23 states and estimated a prevalence rate of 1:133 within the general U.S. population (Fasano et al., 2003). The National Institutes of Health Consensus Development Conference Statement on Celiac Disease currently estimates that 3 million Americans, a little less than 1 percent of the population, may have celiac disease (NIH, 2004). Celiac disease occurs widely among North American and European populations, where wheat is a staple food, but is infrequent among native descendents of China and Japan and those with an African-Caribbean background, where wheat is not as widely consumed (Farrell and Kelly, 2002).
Precise prevalence data for celiac disease are not available. This disease is often misdiagnosed as another gastrointestinal malabsorptive disorder (e.g., irritable bowel syndrome) due to similarities in their symptoms (Sanders et al., 2001). Due to the existence of silent or latent cases, it is assumed that the incidence of celiac disease is underreported (Mäki and Collin, 1997). These forms of celiac disease may go undetected in individuals for years before they develop symptoms causing them to seek medical attention (Green and Jabri, 2003). Mäki and Collin (1997) postulated that there are many more currently healthy individuals who are genetically predisposed to developing celiac disease in future years than there are individuals who are now affected by celiac disease. Only recently has the medical community become more aware of the need to screen for celiac disease when patients experience health problems that may be associated with the disease or when patients have family members, especially first- and second-degree relatives, who have celiac disease (NIH, 2004).
E. Celiac Foods of Concern
Celiac disease is caused by an immune response in genetically predisposed individuals to specific storage proteins, commonly referred to as "glutens," that occur naturally in cereal grains (Shan et al., 2002). Technically, "gluten" is a term applied specifically to the combination of the prolamin proteins called "gliadins" and the glutelin proteins called "glutenins" found in wheat (Brown, 2004). However, the term "gluten" has been used generically to refer to prolamin and glutelin protein mixtures found in other cereal grains (Kasarda, 2005, personal communication). Although all cereal grains contain prolamin and glutelin proteins, these proteins are not identical in different grains. These proteins differ in their amino acid sequences in different grains, and not all have been shown to evoke an abnormal immune response that affects the intestinal lining of persons genetically susceptible to celiac disease (Kasarda, 2003). The term "gluten" will be used in this report in the more general sense of the combination of both prolamin and glutelin proteins found in cereal grains.
The grains considered to be capable of producing adverse effects in individuals with celiac disease include the different species of wheat (e.g., durum, spelt, kamut), barley, rye, and their cross-bred hybrids (e.g., triticale, which is a genetic cross between wheat and rye) (Kasarda, 1994; Kasarda, 2004). There is also evidence that some individuals with celiac disease may react adversely to oats (Lundin et al., 2003; Arentz-Hansen, 2004). These grains are all members of the grass family (Gramineae, also known as Poaceae) and are closely related taxonomically. The cereal grains assumed to be safe for persons with celiac disease include amaranth, buckwheat, corn, Indian ricegrass, Job's tears, millet, quinoa, ragi, rice, sorghum, teff (or tef), and wild rice (Kasarda, 2001; Johnson et al., 2002; Kasarda, 2004b; Kupper, 2004).
The grain prolamins of concern include gliadin in wheat, secalin in rye, hordein in barley (Thompson, 2001; Green and Jabri, 2003; Kagnoff, 2005) and possibly avenin in oats (Arentz-Hansen, et al. 2004; Lundin, et al., 2003). There is substantial evidence that both prolamin proteins (i.e., gliadins) and glutelin proteins (i.e., glutenins) in wheat affect individuals with celiac disease (Shan et al., 2002; Hausch et al., 2002; Vader et al., 2002; van de Wal et al., 1999; Molberg et al., 2003).
Wheat gliadin subtypes alpha, beta, gamma, and omega, have been shown to affect individuals with celiac disease (Ciclitira et al., 1984; EFSA, 2004). Rye, barley and triticale are taxonomically related to wheat, express peptides structurally similar to those found in wheat, and have been reported to affect individuals with celiac disease (Vader et al., 2002; Kasarda, 2001; Kasarda, 2004b). In contrast, the prolamins in other cereal grains (e.g., zein in corn and orzenin in rice) have been shown not to affect individuals with celiac disease (EFSA, 2004; Kasarda, 2004b). However, much is still unknown about which proteins in the different grains can affect individuals with celiac disease (Kasarda, 2001).
Analytical information is not available on the actual amount of gluten proteins in different grain-derived food ingredients or finished foods. For single ingredient foods made from wheat, rye, barley, triticale, and oats, the simple presence of "protein" in that food may be used as an indicator that gluten proteins are present. The USDA National Nutrient Database for Standard Reference, Release 17 (USDA, 2004), the major source of composition data for foods in the U.S., includes hundreds of food items that contain wheat, rye, barley, triticale or oats as an ingredient. Wheat, in particular, is used to manufacture a wide range of food ingredients and finished foods. Rye, barley, triticale, and oats are used to make substantially fewer food products.
Koehler and FDA (2005) estimated the average amount of total grain and individual types of grain available for consumption per person in the U.S., and the total exposure to gluten-forming proteins that would result from this grain consumption. The estimated mean daily consumption rate was approximately 250 grams of grain per capita. Wheat provided 180 of the 187 grams per person per day of grains that are of concern for individuals with celiac disease.
There is no consensus as to whether oats present a hazard for all individuals with celiac disease. Several studies, including one that lasted 5 years, have reported that most celiac study participants tolerated moderate amounts (e.g., 50-70 grams daily) of oats (Janatuinen et al., 1995; Janatuinen et al., 2000; Janatuinen et al., 2002; Lundin et al., 2003; Arentz-Hansen et al., 2004). The oats used by Lundin et al. (2003) and Arentz-Hansen et al. (2004) were tested to ensure that they did not contain any gluten proteins from wheat, rye, or barley.
F. Gluten Contamination of Grains
In the U.S., most commercially available oat products are believed to contain some gluten proteins from wheat, rye, or barley due to cross-contact with these grains during growth, harvest, transport, storage, or processing (Kasarda, 1999; Kasarda, 2001; AGA, 2001; Thompson, 2003). In a recent study, Thompson (2004) analyzed four lots of three brands of rolled or steel-cut oats commercially available in the U.S. for prolamins from wheat, barley, or rye. For one brand, all samples contained 338 to 1807 ppm gluten (expressed as the mean of duplicate determinations). For each of the other two brands, the level of gluten detected in all but one lot ranged from 12-725 ppm in one brand and 120-131 ppm in the other brand (expressed as the mean of duplicate determinations). Thus, only one lot of these two brands was negative for gluten. Thompson (2004) concluded that none of these three brands could be considered a reliable source of oats free of potentially harmful gluten proteins.
Grains that do not contain gluten can become contaminated with grains that contain gluten at any step in the farm-to-table continuum, particularly if shared equipment is not thoroughly cleaned between uses. It is difficult, if not impossible, to prevent all cross-contact situations, considering the tons of grain handled by farm equipment, bulk storage, and transport containers on a daily basis. In fact, the Official United States Standards for Grains (USDA, 1999) assume that most grains that have an established U.S. standard will contain a small percentage of other grains.
G. Gluten Challenge Studies
There is little information in the literature on minimal disease-eliciting doses of gluten for sensitive individuals. Gluten challenges have generally been performed in individuals where diagnosis is uncertain (e.g., infants, Laurin et al., 2002) or in individuals with unclear intestinal pathology results (Wahab et al., 2001). Challenges have also been performed to determine the time of disease relapse after a prolonged period of gluten avoidance (Mayer et al., 1989). In most cases, gluten challenges have been performed to elicit or confirm disease rather than to measure the level of sensitivity (Farrell and Kelly, 2002).
There is no standard protocol for gluten challenges, and challenge studies have varied greatly in amount and duration of gluten exposure. Although some studies have been designed to determine the acute effects (i.e., after 4 hours) of exposure to gluten (Sturgess et al., 1994; Ciclitira et al., 1984), most challenges consist of an open challenge to a fixed or incremental dose of daily gluten over a minimum period of 4 weeks. Many challenge studies use a high exposure (≥ 10 g/day) to gluten, because this is believed to shorten time to disease confirmation or relapse and, therefore, to minimize discomfort to subjects (Rolles and McNeish, 1976). However, some studies have shown that low daily exposures to gluten also can elicit a disease response (Catassi et al., 1993; Laurin et al., 2002; Hamilton and McNeill, 1972).
Catassi et al. (1993) reported that children, whose celiac disease had previously been controlled on gluten-free diet, had evidence of intestinal mucosal or immunological changes (changes in intraepithelial lymphocyte counts and the villous height to crypt depth ratio) following 100 mg or 500 mg of daily gliadin over 4 weeks; this corresponds to 200 mg and 1000 mg of daily gluten respectively (Collin et al., 2004). The degree of inflammation was dose dependent. However, this study had several important limitations, which include the short-term follow up (4 weeks), testing in young children, the small number of subjects (n=20), and the lack of control groups. In addition, although gliadin is believed to be the major immunogenic portion of gluten, T cells from the small intestine of celiac disease patients have been shown to be responsive to peptides from the glutenin portion as well (Van de Wal et al., 1999). Thus, the Castissi et al. (1993) study was also limited by the use of gliadin rather than gluten. Estimating potential harm by extrapolating from gliadin levels may not be representative of the harm from total gluten exposure.
A study currently in progress [The Italian Microchallenge Study] has extended the scope of these earlier findings by evaluating the effects of exposure to either 10 or 50 mg of purified gluten per day for 3 months with a population of 36 celiac disease individuals in a double-blind, placebo-controlled study (Catassi et al., 2005b). Preliminary unpublished results suggest that minimal mucosal abnormalities occur with a strict gluten-free diet, that both 10 mg and 50 mg daily gluten are well-tolerated, but that there is a trend for mucosal changes to occur at the 50 mg dose. These results can be compared to estimated gluten exposures from gluten-free diets containing various levels of gluten contamination (Table III-1, from Collin et al., 2004, reproduced below). Fasano (2005 personal communication) used these values to suggest that a conservative threshold for gluten exposure for sensitive individuals would lie between 20 and 100 ppm.
|Gluten Content in Food (ppma)||Daily Amount of Gluten-Free Food Consumed (g)|
|------Daily Amount of Gluten Consumed (mg)-------|
Source: Collin et al., 2004.
Note: Gluten content in food multiplied by food consumed equals gluten consumed. Six slices of bread is equivalent to approximately 100 g baking mix.
H. Measuring Gluten in Food
Currently, commercial immunology-based ELISA test kits for the detection of gluten in foods are manufactured by Immunotech (Czech Republic), Ingenasa (Spain), Morinaga (Japan), Diffchamb (Sweden), Neogen Corporation (U.S.), R-Biopharm (Germany), and Tepnel BioSystems (U.K.). All of these detect prolamins, the proteins found in soluble aqueous-alcohol extracts from cereals. None is designed to detect all proteins associated with celiac disease. Five of the assays have separately undergone multi-laboratory validation studies (Skerritt and Hill, 1991; Akiyama et al., 2004; Gabrovsk´ et al., 2004; Immer et al., 2003). Each of these studies employed different target levels and matrices. The Tepnel kit was validated by AOAC at >160 ppm gluten (Skerritt and Hill, 1991). All the ELISA kits rely on the preparation of an aqueous-alcohol extracts as analytical samples, and four of the manufacturers include the use of reducing-denaturing conditions for the analysis of baked goods. During the 25th session of the Codex Committee on Nutrition and Foods for Special Dietary Uses in 2003, the R5-Mendez ELISA method, which entails the use of reducing/denaturing conditions, was forwarded to the Codex Committee on Methods of Analysis and Sampling for endorsement (Codex Alimentarius Commission, 2003). These ELISA test kits cross-react, to differing degrees, with prolamins derived from wheat, rye, and barley. None of the test kits cross-reacts with protein extracts from oats (Gabrovsk´ et al., 2004; Nonaka, 2004; Abouzied, 2004; Brewer et al., 2004). As such, the ELISA test kits do not provide protection to individuals with celiac disease who are sensitive to oats (Peraaho et al., 2004; Storsrud et al., 2003; Arentz-Hansen et al., 2004; Lundin et al., 2003). Proficiency testing studies conducted by the Food Analysis Performance Assessment Scheme (FAPAS®) have shown variability between the prolamin ELISA test kits (Central Science Laboratory, FAPAS Series 27 Round 05, Report No. 2705, 2003), indicating that further validation studies for these kits need to be carried out under comparable conditions. In addition to ELISA test kits, two of the manufacturers, Tepnel BioSystems and R-Biopharm, market lateral flow devices for the detection of gluten. To date, neither of these has been validated.
At this time there is no correlative information on the efficacy of using these tests to predict or help prevent adverse effects in individuals with celiac disease.
I. Gluten-Free Labeling
A. General Approaches
|Type of Approach||Examples|
|Analytical methods-based|| |
Labeling of sulfiting agents
"Zero" tolerance policy for Listeria monocytogenes in ready-to-eat foods
|Safety assessment-based||Evaluation of food additive petitions|
|Risk assessment-based||Guidance levels for Vibrio parahaemolyticus in raw oysters|
|Statutorily-derived||Labeling exemption for highly refined oil in the FALCPA|
1. Analytical Methods-Based Approach. In an analytical methods-based approach, thresholds are determined by the sensitivity of the analytical method(s) that can be used to verify compliance. This effectively establishes a "regulatory threshold," although this threshold is not necessarily correlated to biological effects. This approach has been used in food labeling. For example, the requirement to declare sulfiting agents on product labels when foods contain 10 ppm or greater is based on the limit of sensitivity of the analytical method used to measure these agents.
The issues that need to be considered when using an analytical methods-based approach to establish a threshold include:
- What are the sensitivity and specificity of the method?
- Has the method been adequately validated?
- How will the method be used?
- How will the threshold be modified when improved methods are developed?
The strength of this approach is that it is relatively simple, straightforward, and easy to implement. However, it is appropriate to use an analytical methods-based approach to establish thresholds for allergens or gluten only if analytical techniques are available for the food allergen and celiac-associated glutens.
2. Safety Assessment-Based Approach. Safety assessments are routinely applied to public health issues related to substances in foods, such as chemical contaminants or food additives, particularly when a biological threshold can be justified scientifically. The definition of "safe" varies according to the applicable legal provision. For example, for contaminants, the statutory definitions of safety are proscribed in section 402(a)(1). Food is considered adulterated if an added contaminant is in the food in a quantity"...which may render it [the food] injurious to health", or, if the substance is an inherent natural constituent of the food (i.e. "not an added substance") and is in the food in a quantity that would "ordinarily render it [the food] injurious to health". As another example, the phrase "reasonable certainty that no harm will result" is used in section 408 (a)(4) regarding the safety of tolerances for a pesticide chemical residue in or on a food.
For a safety assessment, the term "safety" has connotations involving both the degree of certainty and an assumption of "negligible risk." The prototype chemical safety assessment is the Acceptable Daily Intake (ADI) method which was first articulated by Fitzhugh and Lehman (1954) for use in considering the significance of available animal data. This approach or variations of it are used throughout the world (WHO, 1987). The ADI for a chemical is calculated from the No Observed Adverse Effect Level (NOAEL) and Uncertainty Factor (UF) using the following equation:
ADI = NOAEL / UF.
The same basic methodology can be used to derive other regulatory standards such as Tolerable Daily Intake (TDI), Reference Dose (RfD), and Minimal Risk Level (MRL). These values are derived from controlled animal studies, human clinical studies, or epidemiological studies that provide the exposure level for which there is no apparent adverse effect or which identify the lowest observable adverse effect level (i.e., NOAEL, LOAEL). These adverse effect levels are also considered in conjunction with one or more uncertainty factor(s). Uncertainty factors are applied to account for inter-species and inter-individual differences and other uncertainties in the data (WHO, 2004).
There have been consistent efforts to improve this process to make better use of scientific knowledge. These efforts have focused on both replacing the NOAEL approach and refining the development of uncertainty factors. One example is the development of the benchmark dose (BMD) concept (Crump, 1984; Kimmel and Gaylor, 1988). The BMD concept involves fitting a dose-response model to all the available data and to determine the statistical lower bound of the BMD (i.e., the BMDL). The major advantage of the approach is that the BMDLis not constrained to one of the experimental doses from a controlled study, as is the case with the NOAEL (Crump, 1994). The U.S. Environmental Protection Agency (EPA) uses the BMD method in health risk assessments (Filipsson et al., 2003).
3. Risk Assessment-Based Approach. A risk assessment is a systematic, scientific examination of known or potential adverse heath effects resulting from human exposure to a hazard. The generally accepted paradigm separates risk assessment into four components: hazard identification, exposure assessment, hazard characterization (dose-response), and risk characterization. This framework allows for organization of information, definition of uncertainties, and identification of data gaps. Risk assessments can describe the likelihood of adverse health effects either quantitatively or qualitatively depending on the extent of the knowledge available, the complexity of the problem, and the time available to conduct the assessment. In quantitative risk assessments, risk is expressed as a numerical estimate of the chance of illness or death after exposure to a specific hazard. This estimate represents the cumulative probabilities of certain events happening and the uncertainty associated with those events. A qualitative risk assessment, on the other hand, uses verbal descriptors of the risk and uncertainties, and often involves the aggregation of expert opinions.
Of the four approaches, the quantitative risk assessment-based approach is the most scientifically rigorous and provides insight into the level of risk associated with specific exposures and the degree of uncertainty inherent in the risk estimate. An example of the use of a risk estimate and associated uncertainty is the current standard for hypoallergenic infant formulas, where there is 95% certainty that 90% of the sensitive population will not react (American Academy of Pediatrics, 2000). The risk assessment-based approach is preferred when a biological threshold cannot be justified scientifically. Several recent papers have discussed the application of the risk assessment-based approach to food allergens (Bindslev-Jensen et al., 2002; Moneret-Vautrin and Kanny, 2004; Cordle, 2004; Wensing et al., 2002a).
The issues that need to be considered when using a risk assessment-based approach include:
- What is the biological endpoint or biomarker of concern?
- Is the response measurable?
- What is the population (or sub-population) of interest?
- What are the exposure levels?
- What data and assumptions are needed for the assessment, and how do gaps in the existing data affect the level of uncertainty?
Other issues that should be considered in regard to understanding the relationship between the exposure level and nature of the response include:
- How sensitive and accurate are the available analytical methods?
- How do changes in individual sensitivities over time and within populations contribute to the overall uncertainty?
- What are the limitations of the clinical studies (e.g., small number of volunteers, not testing the most sensitive subpopulation) that are used to determine the dose-response relationship and how do these limitations contribute to the overall uncertainty?
- Which dose-response models (e.g., threshold, non-threshold) are appropriate?
It is not clear whether the data and modeling techniques available at the present time are sufficient to allow use of the risk assessment-based approach to establish thresholds for food allergens and for gluten. As an example of the complexity of this approach, the following describes the process of developing a dose-response model that can be used in a quantitative risk assessment:
Steps in Developing a Dose-Response Model
- Determine the population of concern (e.g., infants, children, pregnant women).
- Determine the endpoint or biomarker of concern (e.g., death, severe illness requiring hospitalization, subjective reactions such as tingling of lip).
- Identify available relevant data including animal studies, human clinical studies, and epidemiological data that relate dose to frequency or severity of response.
- Select the appropriate dose-response model(s) that characterize the shape of the dose-response curve.
- Fit the selected model(s) to the data.
- Characterize the uncertainty (i.e., curve weighting and/or use of alternative plausible models).
4. Statutorily-Derived Approach. The statutorily-derived approach establishes a threshold by extrapolating from an exemption established by Congress for another purpose. For example, the FALCPA defines "major food allergen " to include a food ingredient "that contains protein derived " from one of eight foods or food groups, "except... any highly refined oil " derived from one of those foods. If consumption of highly refined oils is not associated with allergic reactions, and if there is nothing unique about the proteins in highly refined oils, then consumption of another food containing levels of protein that result in an exposure that is equal to or less than the level in a typical serving of highly refined oils should not be associated with allergic reactions. Thus, a threshold could be established for all food allergen proteins based on the level of protein in highly refined oils. There is no comparable statutory standard for gluten.
B. General Criteria for Evaluating and Selecting Approaches to Establish Thresholds
|Data Availability||Identification and review of currently available data that can be used in any of the four approaches to establish a specific threshold.|
|Data Quality||Evaluation of the available data for utility, completeness, and scientific soundness. Evaluation of the degree of uncertainty associated with the data.|
1. Feasibility. The published and unpublished literature summarized in Sections II and III of this report were reviewed to determine the availability of the specific types of data needed for each of the approaches to establish thresholds. When necessary information was not available, the following questions were used to evaluate the existing information:
- Is there surrogate or alternate information available that could be used?
- Is the existing knowledge sufficient to support reasonable assumptions when specific data are not available?
- What is the level of uncertainty associated with these data and assumptions?
2. Uncertainty. Uncertainty is typically thought to arise from the lack of data or information. Other sources of uncertainty are often considered to be relevant to scientific evaluations such as subjective judgment, statistical variation, sampling errors, and inherent randomness (Byrd and Cothern, 2000). Techniques are available to account for or measure some of these uncertainties. For example, the uncertainty in a dose-response model can be characterized using advanced techniques, such as model weighting, that measure the degree of credibility associated with the model results (Carrington, 1997). State-of-the-art food safety risk assessment models, such as the HHS/USDA Listeria monocytogenes risk assessment for ready-to-eat foods (HHS/USDA, 2003) also used techniques that separate uncertainty from biological variability. It is important to note that uncertainty is different from variability. Uncertainty reflects incomplete knowledge about a system or population which can be reduced with additional study. Variability reflects the fact that all systems or populations have inherent, biological heterogeneity that is not reducible through further measurement or study (Voysey et al., 2002). Sufficient knowledge is needed to account for both variability and uncertainty in order to evaluate the four approaches for establishing thresholds.
As described above, uncertainty factors are used in safety assessment calculations. Fitzhugh and Lehman (1954) originally proposed a single safety factor of 100-fold applied to animal data. The justification for this factor included both scientific issues and social values. The scientific issues included the possibility that humans may be more sensitive to chemicals than the rodents used in laboratory tests and that there may be substantial variability among individuals in a population. In general, as uncertainty increases, the uncertainty factor employed in a safety assessment should increase proportionally. As a matter of practice, uncertainty is not characterized in a safety assessment, either formally or subjectively, as is done in a quantitative risk assessment. A minimum uncertainty factor of 10 is generally used to account for variation within the population when relying on human data and additional uncertainty factors may be included as appropriate. For example, the Food Quality Protection Act (FQPA) of 1996 requires, in certain cases, a 10-fold factor in addition to any other uncertainty factors to protect infants and children from exposure to pesticides. Similarly, the EPA uses uncertainty factors of 3 for inter-species differences,10 for variability among humans (intra-species variability), 10 for extrapolation from subchronic to chronic exposures, 10 for extrapolation from LOAELs to NOAELS, and 1 to 10 for data deficiencies in safety assessments related to continuous inhalation exposures (U.S. EPA, 2002; Jarabek, 2002). The assignment of uncertainty factors should be based on science but typically will include the application of expert judgment.
3. Data Quality. The FDA Information Quality Guidelines and the Agency for Healthcare Research and Quality (AHRQ) guidelines on systems for rating the strength of scientific evidence were used in evaluating the scientific data contained in this report (West et al., 2002). The FDA guidelines describe policies and procedures for ensuring the quality of the information disseminated by FDA. In these guidelines, data quality is defined in terms of utility, objectivity, and integrity. Utility is defined as the usefulness of the information to its intended users; objectivity as presentation of the data in an accurate, clear, complete, and unbiased manner; and integrity as protecting the information from unauthorized access or revision. In particular, the guidelines provide transparency standards and ensure clarity. The AHRQ guidelines describe systems for evaluating the strength of scientific studies, including randomized clinical studies. In these guidelines, quality is defined as "the extent to which a study's design, conduct, and analysis has minimized selection, measurement, and confounding biases." In addition, the AHRQ guidelines suggest specific factors (called Domains and Elements) that should be considered in evaluating individual studies. These factors were considered in developing the criteria described below.
C. Allergen Thresholds: Evaluation and Findings
This section provides an evaluation of the data needed to establish thresholds for the major food allergens. Based on the availability and quality of the data, the Threshold Working Group provides findings that can be applied to establish such thresholds.
1. Evaluation of Data Availability and Data Quality
a. Sensitive Populations. Individuals within an allergic population express a wide degree of sensitivity to low dose allergen exposures. Moreover, the individuals who react to low dose allergen exposures may also have the most severe reactions following these exposures. Thus, there may be a distinct, highly sensitive population within the general population of food allergic individuals. Because most clinical studies exclude patients who have had previous anaphylactic reactions or who have high specific IgE titers, it is possible that the most sensitive individuals within the allergic population may be systematically excluded from these studies. Therefore, it is possible that the doses reported to elicit "initial objective signs" are higher than would be expected for the entire allergic population. The observed data may also not be representative of the allergic population in studies that use patient populations that are not known to be allergic to the food being tested (e.g., testing milk allergic patients for sensitivity to soy). In addition, individual sensitivity varies over time and "high sensitivity" may be a transient condition for an individual.
There are a number of case reports in the scientific literature documenting allergic reactions to incidental exposures to allergens. These reports are difficult to interpret because the level of exposure and potential influence of other factors (e.g., medications, exercise) are not known. Nevertheless, if these reports document true allergic reactions, this suggests that these individuals could be considered to be highly sensitive when compared to the general population of food allergic individuals.
Based on currently available data, the Threshold Working Group was unable to identify any scientifically-based studies that indicate that the standard 10-fold uncertainty factor used in safety assessments for inter-individual variability is not adequate to account for variation within the sensitive population. However, because of the limitations in the clinical studies and the case reports discussed above, this assumption should be reexamined as more data on the distribution of sensitivities within the population become available.
b. Biomarkers. Because there are no in vitro markers that can be used to assess the severity of an allergic reaction, and a number of different signs and symptoms are associated with allergic reactions, clinical symptoms elicited during challenge are currently viewed as the best indicators, or biomarkers, of an allergic response. The manifestations of an allergic reaction can be either subjective (reported by the patient but not overtly measurable) or objective (overt reactions that are observed or measured by another person). Objective signs vary on a continuum of severity from mild rashes to fatal anaphylaxis. Although each of these is an "adverse effect," there is no consensus about where on this continuum they become "serious adverse effects." This makes it difficult to apply either risk assessment- or safety assessment-based approaches to establish thresholds for food allergens because both approaches require that the adverse end point be well defined.
Most clinical studies expose patients to increasing doses of an allergen until the first objective sign is observed. This is often, but not always, a relatively mild reaction. For ethical and technical reasons, few studies measure dose-response relationships for individual patients beyond the initial objective sign. Therefore, the currently available literature provides data based on the "initial objective sign." Although the "initial objective sign" is the biomarker measured in most available allergen clinical studies, it is unclear whether these signs are consistently considered across these studies. It is also not clear whether and when subjective reactions should be considered "adverse effects," or should influence the selection of a NOAEL or LOAEL for safety assessments.
Normally, the use of the "initial objective sign" would lead to threshold values that are "protective" in relation to the overall risk to food allergic consumers. However, it should be noted that severe reactions have been reported as the initial objective sign in some cases. For example, Perry et al. (2004) reported that almost 30% of initial reactions were severe and stated that "reaction severity did not increase as the amount of challenge food ingested increased." Likewise, the only severe reaction observed by Hourihane et al. (1997a) in a population of 100 patients occurred at the lowest dose tested. However, considering that the use of the "initial objective sign" does appear to be generally protective, and that such data would be used in conjunction with appropriate uncertainty factors, it may not be necessary to differentiate among "mild," "serious," or "life-threatening" signs when establishing a safety assessment-based threshold from existing clinical data.
c. Analytical Methods for Food Allergens. The criteria used to evaluate the available analytical methods for the major food allergens are shown in Table IV-3 and are applied in Appendix 1.
|1. Has the method been validated?||Methods that have been validated (such as by AOAC) are preferred. Alternatively, the sensitivity, precision, and reproducibility of the method have been demonstrated in a peer-reviewed publication.|
|2. Is the method sufficiently sensitive?||The limit of detection and the limit of quantitation should be below the levels that appear to cause biological reactions.|
|3. Does the method detect both raw and processed food allergens?||The relevant processing methods (e.g., boiling, roasting, retorting) will depend on the food.|
|4. Has the species specificity of the method been determined?||This is most relevant to methods for allergens such as fish and tree nuts.|
|5. Has the protein target (or targets) for the method been determined?||This is relevant to determining whether the assay detects specific allergenic proteins or general biomarkers.|
|6. Is the method practical?||The method should use common laboratory equipment and supplies.|
The response of sensitive consumers to exposure to an allergen is dependent on the levels of the allergen in the food and the amount of food consumed, two factors for which there is both variability and uncertainty. The levels of allergen in foods may not be known for a number of reasons, particularly when the presence of the allergen is the result of cross-contact. Even in highly controlled clinical studies, questions regarding the level of allergen arise due to differences in the methods used to process and prepare the test material, incomplete characterization of this material, variability in allergen levels among different sources of the food, lack of standardized reference materials, and differences in the analytical methods used to quantify the levels of the allergen.
The methods used to quantify and express the doses received during clinical studies and adverse event investigations are not consistent, and this increases the uncertainty associated with the available data. The amount of an allergen consumed has been described in terms of total weight of a food consumed, total protein from an allergenic ingredient, or amount of specific allergenic proteins. Although the last description is scientifically the most accurate, it is also the most difficult to use because not all individuals are allergic to the same proteins in a food allergen and all the allergenic proteins may not have been identified for a particular food. Measurements based on the whole foods are simple, but increase the level of uncertainty because the composition of the food may vary. For example, changes in water content of a food would change the relative amount of allergenic protein present in serving sizes of a specified mass. Further, the amount of protein present as a percent of the total weight of the food may vary due to maturation, environmental factors, seasonal factors, production variability, or between different cultivars or strains. The Threshold Working Group recognized that the scientifically most accurate means of assessing exposure would be to quantify individual allergenic proteins, but concluded that the most practical approach for evaluating the currently available data is to measure exposure in terms of the total protein from a food allergen. This is also consistent with current technology for detecting food allergens.
It should also be noted that, while clinical exposures are expressed in terms of doses (i.e., g, mg, or μg), allergen levels in foods are actually measured as concentrations (i.e., ppm, percent, or mg/kg). These values can be related by defining a standard serving size, usually 100 g. However, it is well documented that the actual serving eaten by consumers should be treated as a variable and a source of uncertainty when assessing exposures.
d. Challenge Studies. Clinical food challenge studies are recognized to be the most accurate way to diagnose allergies and to measure sensitivity to an allergen (Sampson, 2005). Unfortunately, the design of these food challenge studies varies widely. The lack of standardized protocols, variations in the dosing regimes (including number of doses, the interval between doses, and the relative size of the doses), and differences in the food sources (including differences in preparation and presentation) result in uncertainties when comparing the results of different studies. Double-blind placebo-controlled food challenges (DBPCFC) are considered the most robust clinical studies and data from these studies should be given preference whenever they are available. Food challenge studies are generally not designed to determine a lack of reaction (i.e., NOAEL). Instead, the doses that produce positive allergic reactions are generally reported, providing an estimate of the LOAEL for the population being studied. Despite the uncertainties associated with food challenge data from the literature, LOAELs from human clinical trials currently provide the best data for estimating population-based reactions to food allergens. In a safety assessment-based approach, the use of LOAELs instead of NOAELs would introduce additional uncertainty. A standard DBPCFC protocol has been proposed to identify NOAELs for various food allergens, but few publicly available, peer-reviewed data of this nature are available at this time.
The specific criteria used to evaluate food challenge studies are shown in Table IV-4, and applied in Appendix 2.
|1. Has the study been published in a peer-reviewed journal?||Published, peer-reviewed studies are preferred although unpublished studies may be considered.|
|2. Were the criteria for selecting the test population clearly and completely described, and are they appropriate?||This information is needed to evaluate how the study results apply to at-risk populations (i.e., was the tested population allergic to the tested food?).|
|3. Was the test material clearly and completely described?||This information is needed to determine the amount of allergenic protein in the test material.|
|4. Was the lowest tested dose of allergen described, or can it be calculated?||This information is needed to determine a NOAEL or LOAEL.|
|5. Were the total number and progression of dose levels described, or can they be calculated? (i.e., can the entire dose series be explicitly determined?)||This information is not needed for a safety assessment, but is needed for a risk assessment.|
|6. Did some of the test population respond to the lowest dose?||NOAELs and LOAELs cannot be determined in studies in which reactions occurred at the lowest dose tested.|
|7. Were the allergic reactions observed clearly described?||Objective reactions are preferred for both safety and risk assessments.|
|8. Were the data sufficient to describe the dose-response pattern for the population tested (e.g. for determining a cumulative dose-response curve)?||This information is needed for a risk assessment.|
e. Differences Among Food Allergens. Allergens differ widely both in their potential to elicit allergic reactions and in the severity of these reactions. The simplest approach to dealing with these differences would be to establish a single threshold based on sensitivities to the most potent allergens. This threshold is likely to be unduly restrictive for many allergic consumers. Alternatively, separate thresholds could be established for each food allergen. However, the data needed for the separate threshold approach are not available for many allergens. The Threshold Working Group concluded that, to the extent possible, each food allergen should be treated independently but that a single threshold should be established if independent treatment is not possible. If a single threshold is established, it could be based on the allergenic food that elicits an allergenic reaction at the lowest total protein level.
Some of the major allergens identified in the FALCPA consist of multiple species (i.e., tree nuts, fish, crustacean shellfish). Because consumers who are sensitive to one species in a group are also likely to be sensitive to other members of the group, the Threshold Working Group concluded that any thresholds established for these allergens should be based on the combined amount of protein from these species present.
f. Processing and Matrix Effects. Most of the food allergens identified in the FALCPA are eaten in a processed form. The existing data show that processing can increase, decrease, modify, or have no affect on allergenicity depending on the allergen, the process, and the matrix involved. A process that modifies the structure of an allergenic protein could reduce allergenicity for one population of susceptible individuals while simultaneously increasing allergenicity for a separate susceptible population.
Most clinical studies are conducted using test materials that have been processed, such as peanut butter prepared from roasted peanuts. Therefore, these studies are likely to mimic actual consumer exposure to the allergen. However, some uncertainty remains because consumers are exposed to food allergens processed in many different ways and in many matrices. It would not be practical to conduct the large number of clinical studies that would be necessary to reduce this uncertainty. Fish appears to be an important exception because raw fish is often used as a test material. Most people eat cooked fish and this should be taken into account when evaluating the results of these studies.
2. Options and Findings
There are four general approaches that could be used to establish thresholds for food allergens - analytical methods-based, safety assessment-based, risk assessment-based, and statutorily-derived. Each approach has strengths and weaknesses, and the application of each is limited by the availability of appropriate data. It is likely that there will be significant scientific advances in the near future that will address a number of the limitations identified in this report. The Threshold Working Group was aware of several potentially important studies that are currently in progress, but was unable to fully consider them because the data or analyses were incomplete.
Finding 1. The initial approach selected to establish thresholds for major food allergens, the threshold values, and any uncertainty factors used in establishing the threshold values should be reviewed and reconsidered periodically in light of new scientific knowledge and clinical findings.
a. Analytical Methods-Based Approach. The analytical methods-based approach could be used to establish thresholds if the available data are insufficient to establish thresholds using one of the other approaches. This approach requires that analytical methods be available to detect each major food allergen. Thresholds would be defined by the limits of detection of the available analytical methods, but there would be no relationship between these thresholds and the biological response thresholds. Currently, the lower detection limits for commercially available allergen ELISA or immunoassay test kits are in the range of 0.1 to 1.0 µg protein/g of food, but such kits are not available for all food allergens. Establishing thresholds at levels higher than the lower detection limits of the analytical methods would require the use of assumptions about the biological response thresholds. In that case, the thresholds are actually based on using another approach and should not be considered an analytical methods-based threshold.
Advantages. When accurate, validated methods are available to measure food allergens, determining a threshold based on these methods can be a straightforward way to establish that products are in compliance with this defined level.
Limitations. There are several disadvantages to using this approach in determining thresholds for food allergens:
- The approach is not risk-based and it is likely that the appropriateness of any thresholds established using this approach will be questioned as existing methods are improved or new methods are developed. Further, in the absence of information on biological response thresholds, it is difficult to assess how well thresholds established using this approach protect public health.
- Validated analytical methods are currently not available for all of the major food allergens. However, this is likely to change rapidly if there is a need for such analytical capability.
- There is uncertainty as to the performance of the available analytical methods in the wide variety of food matrices that are likely to be encountered. Theoretically, the test methods should be validated for all foods and food matrices, but this is not practical.
- Current methods, which are based on a food's total protein content, will not be sufficient in the future if techniques and technologies for reducing the levels of specific allergenic proteins are developed.
Presumably, the analytical methods used to establish thresholds in this approach could also be used to evaluate compliance with any applicable legal requirements. However, the ability to use these methods to help prevent the introduction of unlawful product into the market place would require that the methods be applied in a scientifically supportable manner. This would require the establishment of a statistically supportable sampling plan. The cost of the sampling to a degree sufficient to provide reasonable statistical confidence is potentially an issue.
Finding 2. The analytical methods-based approach could be used to establish thresholds for those food allergens for which validated analytical methods are available. However, if this approach is used, the thresholds should be replaced by thresholds established using another approach as quickly as possible.
b. Safety Assessment-Based Approach. The safety assessment-based approach could be used to establish thresholds based on NOAELs or LOAELs reported in the literature in combination with appropriate uncertainty factors. Because very few publications report NOAELs or present results in a form that allows NOAELs to be calculated, this type of analysis would, for most food allergens, be based on LOAELs. NOAELs should be used when they are available or can be calculated (see Appendix 2).
As discussed previously, there are substantial differences in the relative potency of different food allergens (e.g., peanut vs. soy). As noted in Appendix 2 and summarized in Table IV-5, the reported LOAELs for peanuts are considerably lower (maximum of 10 mg protein) compared to soy (maximum 522 mg protein). A single threshold for food allergens, based on the most potent food allergens, could be employed if, as a matter of risk management policy, a single threshold is considered desirable. However, this could be considered overly protective, particularly in the case of soy.
|Food||Range of LOAEL (mg protein)|
|Egg||0.13 to 1.0|
|Peanut||0.25 to 10|
|Milk||0.36 to 3.6|
|Tree Nuts||0.02 to 7.5|
|Soy||88 to 522|
|Fish||1 to 100|
Advantages. Calculation of threshold levels based on NOAELs or LOAELs and the application of appropriate uncertainty factors to estimate exposure is relatively straightforward. When there are limited data in the literature, the application of appropriate uncertainty factors provides confidence that the majority of the sensitive populations will be protected. For a number of the major food allergens, there is reasonably good agreement among the reported LOAEL values. Establishing thresholds using the safety assessment-based approach and currently available clinical data has the advantage of being directly linked to biological effects.
Limitations. There are limited clinical trial data for most allergens and most available clinical food challenge studies have not been designed to identify a NOAEL. Furthermore, an inherent, but unexamined, assumption in all clinical studies is that the reactions seen in a clinical setting are representative of the reactions to food allergen exposure that occur in the real world. Most available clinical data are primarily limited to identifying LOAELs, and there is no way to know whether doses below the observed LOAEL would still elicit a reaction. Thus, the selection of appropriate factors to account for uncertainty and inherent variability is critical in using the safety assessment-based approach. Until there is a consensus as to whether subjective symptoms are acceptable biomarkers or which objective signs are considered harmful, it appears prudent to consider as adverse any objective reaction observed in a clinical trial.
We have identified several data gaps for allergens that add to the uncertainty associated with setting thresholds. Critical areas of uncertainty and variability include:
- Intraspecies differences. Safety assessments typically apply a 10-fold uncertainty factor to account for the variability both between individuals and variability in responses for a particular individual.
- Sensitive population of interest. The existence and size of highly sensitive subpopulations of allergenic individuals and their lack of participation in reported clinical trials is a potential data gap and should be included in the uncertainty factors. It is unclear whether the standard 10-fold uncertainty factor for variability within a species is sufficient to account for potential highly sensitive subpopulations. Because of the potential severity of reaction for this subpopulation it seems prudent to include an additional margin of safety (e.g., a 10-fold uncertainty factor) for this uncertainty. It is not unusual for safety assessments to provide additional protection for susceptible populations. For example, EPA uses an additional safety factor in reevaluating pesticides as per the Food Quality Protection Act (FQPA, 1996) to account for the greater susceptibility of children to certain pesticides.
- Adequacy of clinical trial data. Most of the available data from clinical trials report LOAELs. There is uncertainty associated with using LOAELs rather than NOAELs to establish a threshold. For peanuts, one of the few food allergens for which NOAEL values are available, the LOAELs for objective signs are approximately 2 to 3 fold greater than the NOAELs.
- Other. Additional data gaps have been identified by the Threshold Working Group; however, concluded that uncertainties associated with these factors were not sufficient to warrant additional uncertainty factors. These data gaps include the following: (1) the use of total protein from a food as a surrogate for measuring the level of specific allergenic proteins in clinical trials; (2) variability in serving sizes and related exposure factors; and (3) the incompletely defined effects of food processing on the levels and reactivity of allergenic proteins.
The Threshold Working Group acknowledges that it is difficult to estimate uncertainty factors that apply in all situations for all allergen threshold determinations when using a safety assessment-based approach. We can, however, assume that a standard uncertainty factor of 10-fold should be applied for intraspecies differences in humans. Additional uncertainty factors could be added if justified from data gaps. In Table IV-6, we use peanuts, widely considered to be among the most potent food allergens, to illustrate how specific uncertainty factors may be developed for use in a safety assessment-based approach to set a threshold if that approach is adopted.
|Intraspecies difference1||10||Standard factor for intraspecies variability|
|Estimation of NOAEL2||Not applicable||Two studies were identified that report NOAELs|
|Sensitive population3||10||Used to account for additional margin of protection for more susceptible populations not included in clinical trials|
|Overall Uncertainty Factor for Peanuts = 100|
1 This includes both between- and within-individual variability.
2 This includes both a factor for converting the LOAEL to a NOAEL and an additional factor for the uncertainty associated with that conversion. In this example for peanuts, there are data on both subjective and objective NOAELs and LOAELs. If the NOAEL values are used, the uncertainty factor is 1-fold (i.e., not applicable). If the LOAELs had been used, this value would have been higher. If subjective symptoms observed at lower levels are used, a different uncertainty factor may be considered.
3 This includes uncertainty associated with an additional margin of protection to account for the potential severity of reaction (e.g., lethality) for the highly sensitive subpopulation.
Finding 3. The safety assessment-based approach, based on currently available clinical data, is a viable way to establish thresholds for food allergens. If this approach is employed, the LOAEL or NOAEL determinations used should be based on evidence of the "initial objective sign." Individual thresholds should be established for each of the major food allergens. If it is not feasible to establish individual thresholds, a single threshold based on the most potent food allergens should be established. In those instances where a LOAEL is used rather than a NOAEL to establish a threshold, an appropriate uncertainty factor should be used. Thresholds established using this approach should be reevaluated periodically as new data and tools become available.
c. Risk Assessment-Based Approach. The use of the risk assessment-based approach requires analysis of the population distributions of allergic sensitivities for each of the major food allergens. These distributions would then be used in conjunction with data on exposures to assess the probability of an adverse effect. These distributions could also be used to evaluate the likely efficacy of different risk reduction strategies.
Advantages. The quantitative risk assessment-based approach is the most scientifically rigorous approach and provides the most insight into both the level of protection and the degree of uncertainty associated with an exposure level. Several recent publications that present preliminary quantitative risk assessments based on data from clinical trials suggest that this approach shows promise (Bindslev-Jensen et al., 2002; Moneret-Vautrin and Kanny, 2004; Cordle, 2004; Wensing et al., 2002a).
Limitations. Quantitative risk assessments require the most data of any approach to establish thresholds for food allergens, because they are based on determining the entire dose-response curve, not simply a NOAEL or LOAEL. The data currently available in the literature for food allergens are generally not detailed enough to be useful for quantitative risk assessment. Further, the underlying mathematical procedures and assumptions have not been fully described for the models that have been published. No consensus has been reached regarding the most appropriate mathematical model to use for analyzing allergen reaction data.
Finding 4. Of the four approaches described, the quantitative risk assessment-based approach provides the strongest, most transparent scientific analyses to establish thresholds for the major food allergens. However, this approach has only recently been applied to food allergens, and the currently available data are not sufficient to meet the requirements of this approach. A research program should be initiated to develop applicable risk assessment tools and to acquire and evaluate the clinical and epidemiological data needed to support the quantitative risk assessment-based approach. Thresholds established using this approach should be reevaluated periodically as new data and tools become available.
d. Statutorily-Derived Approach. As discussed above, an allergen threshold could be extrapolated from a statutory exemption established by Congress for another purpose, such as the FALCPA exemption for "highly refined oils." Thus, a threshold could be established for all food allergen proteins based on the level of protein in highly refined oils.
There are surprisingly few data available in the published scientific literature reporting on the levels of proteins in highly refined oils. The criteria used to evaluate studies measuring protein levels in food oils are shown in Table IV-7 and applied in Appendix 3.
|1. Has the study been published in a peer-reviewed journal?||Published, peer-reviewed studies are preferred, although unpublished studies can be considered.|
|2. Was the oil completely described, including all refining and treatment steps?||The level of processing must be known both to compare values among studies and because each processing step may change the level of protein in oil.|
|3. Was the method used to extract the protein completely described?||Extraction procedures should be described in sufficient detail to allow the extraction to be reproduced and, ideally, extraction efficiencies should be measured and reported.|
|4. Was the method used to quantify protein levels completely described?||The lack of these data increases the level of uncertainty.|
|5. Were replicate samples or batches tested, and was there a statistical analysis of these data?||The lack of these data and statistical analysis increase the level of uncertainty.|
Based on the data presented in those studies that reported levels other than "not detected," the overall range of protein concentrations for highly refined oils was 0.014 to 16.7 µg protein/ml oil, with a mean of 2.35 µg/ml. The combined mean protein concentration for the two most widely used oils derived from food allergens, soy and peanut, is 0.74 µg/ml with a standard deviation (std) of 1.3 µg/ml. A threshold could be based on the mean protein concentrations or on the mean plus some multiple of the standard deviation. For example, using the mean protein concentrations for peanut and soy oils, protein levels for the mean, mean + 1 std, mean + 2 std, or mean + 3 std would be the 0.74, 2.05, 3.36, and 4.67 µg/ml, respectively.
Advantages. The primary advantage to the statutorily-derived approach is that it is derived from FALCPA's exemption for highly refined oils from labeling provisions in the FALCPA.
Limitations. The primary limitation of this approach is that it is based on an extrapolation of a level derived from a statutory exemption rather than a rigorous, systematic evaluation of all the available scientific data. Because not all the eight major food allergens are used to produce highly refined oil, the use of a statutorily-derived threshold for all food allergens would be based primarily on the protein levels in highly refined soy or peanut oil. Another current significant limitation is the lack of data on the levels of protein in highly refined oils. Based on the data that are currently available and estimates of the amount of oil consumed as a food or food ingredient, it is likely that a threshold based on this approach would be unnecessarily protective of public health.
Finding 5. The statutorily-derived approach provides a mechanism for establishing thresholds for allergenic proteins in foods based on a statutory exemption. Potentially, this approach could be used to set a single threshold level for proteins derived from any of the major food allergens. This approach might yield thresholds that are unnecessarily protective of public health compared to thresholds established using the safety assessment-based approach or the risk assessment-based approach. However, confirming this would require additional data. If this approach is employed to establish thresholds, it should be used only on an interim basis and should be reevaluated as new knowledge, data, and risk assessment tools become available.
D. Gluten Threshold: Evaluation and Findings
Section 206 of the FALCPA requires that the term "gluten-free " be defined for use on food labels. The law neither describes how gluten-free should be defined nor states whether there is a safe level of gluten.
This section provides an evaluation of the available data to support various approaches for establishing a threshold for gluten. A threshold, if established, could be the basis for decisions on whether to use the term "gluten-free" on product labels.
1. Evaluation of Data Availability and Data Quality
a. Sensitive Populations. Like food allergies, celiac disease affects only a small proportion of the U.S. population (estimated at 1%) (NIH, 2004). Susceptibility to celiac disease is genetically determined and is linked to the presence of the DQ2 or DQ8 HLA alleles. However, carrying these alleles does not necessarily lead to celiac disease. Both acute and chronic morbidity have been well documented for individuals with symptomatic celiac disease. A gluten-free diet has been shown to greatly reduce the risk for cancer and overall mortality for these individuals. The potential benefit of a gluten-free diet has not been established for individuals with silent or latent celiac disease.
b. Biomarkers. Unlike food allergies, clinical signs and symptoms do not appear to be reliable markers of disease activity because many individuals affected with celiac disease may be entirely asymptomatic. Furthermore, although biomarkers of genetic susceptibility (e.g., presence of DQ2 and/or DQ8 HLA alleles) and gluten exposure [e.g., antibodies for gliadin (AGA), endomysial (EMA), and tissue transglutaminase (tTG)] have been defined for use in noninvasive diagnosis of individuals with celiac disease, these biomarkers have not been shown to correlate with disease severity nor to be useful in assessing daily responses to gluten exposures. Rather, evidence of intestinal mucosal inflammation is the gold standard biomarker for diagnosis of celiac disease and for assessment of disease severity. Intestinal mucosal inflammation may occur long before the development of clinical signs or a rise in antibody titers following a gluten challenge. Intestinal inflammation is assessed by intestinal biopsy, which is an invasive procedure, associated with false negatives (due to sampling error), and is impractical for frequent monitoring of disease activity or severity.
c. Foods of Concern. The foods of concern for individuals with, or susceptible to, celiac disease are the cereal grains that contain the storage proteins prolamin and glutelin (commonly referred to as glutens in wheat), including all varieties of wheat (e.g., durum, spelt, kamut), barley (where the storage proteins are called hordiens), rye (where the storage proteins are called secalins), and their cross-bred hybrids (such as triticale). The proportion of individuals with celiac disease that are also sensitive to the storage proteins in oats (avenins) has not been determined but is likely to be less than 1% (Kelly, 2005).
d. Methods of Analysis. The criteria used to evaluate the available methods of analysis for gluten in food are shown in Table IV-8 and are applied in Appendix 4. A number of commercial immunology-based ELISA test kits for the detection of gluten in foods are available, and one has been validated by AOAC (the Tepnel kit, validated at 160 ppm). One limitation of these kits is that they only detect prolamins. This is not likely to limit the detection of gluten in foods because in most cases prolamins and glutelin occur together. However, it may lead to an underestimate of the level of gluten present. Also, none of the test kits cross-reacts with protein extracts from oats, which limits their efficacy for the small portion of celiac patients who are also sensitive to oats. Test kits suitable for the detection of oat proteins should be developed. .
|1. Has the method been validated?||Methods that have been validated (such as by AOAC) are preferred. Alternatively, the sensitivity, precision, and reproducibility of the method should have been demonstrated in a peer-reviewed publication.|
|2. Is the method sufficiently sensitive?||The limit of detection and the limit of quantitation should be below the levels that appear to cause biological responses in most patients with celiac disease.|
|3. Are extraction methods available for both raw and baked foods?||Different methods may be needed; each should be validated.|
|4. Does the method measure proteins from all relevant foods?||The cereal grains associated with celiac disease include wheat, barley, rye, and their cross-bred hybrids. Oats may be of concern for some celiac patients.|
|5. Does the method measure both gliadins and glutenins?||The storage proteins in cereal grains (generally referred to as gluten) include both prolamin proteins (gliadins) and glutelin proteins (glutenins). Ideally, both of these should be measured.|
|6. Is the method practical?||The method should use common laboratory equipment and be reasonably priced.|
|1. Has the study been published in a peer-reviewed journal?||Published, peer-reviewed studies are preferred although unpublished studies may be considered.|
|2. Were the criteria for selecting the test population clearly and completely described?||This information is needed to evaluate how the study results apply to the at-risk population.|
|3. Was the tested food material clearly and completely described?||It is important to know the level of gluten in the test material.|
|4. Was the dose regime clearly and completely described?||A study designed to measure chronic exposure (low doses over a long period of time) is preferable. Extrapolation of long-term effects from short-term studies increases the level of uncertainty.|
|5. Were the criteria for characterizing responses clearly described?||This information is needed to evaluate the relevance of the response measured. A definitive diagnostic assessment showing clinical signs or intestinal mucosal changes compared to controls is preferred.|
|6. Are response data available for each individual tested?||These data are needed to develop a risk assessment-based dose-response model.|
2. Options and Findings
The feasibility of using each of the four methods to establish a threshold for gluten was evaluated in light of the available data. As with food allergens, it is likely there will be significant scientific advances in the near future that will address a number of the limitations identified in this report. The Threshold Working Group was aware of several potentially important studies that are currently in progress, but we were unable to evaluate them because the data or analyses are incomplete.
In particular, the Threshold Working Group is aware of unpublished data from an ongoing clinical trial of the subchronic effects of gluten on celiac patients. The "Italian Microchallenge Study" is utilizing intestinal biopsies to relate changes in the intestinal mucosa to antibody biomarkers (Fasano, 2005 personal communication). Preliminary results indicate that daily consumption of both 10 mg and 50 mg of dietary gluten were well tolerated after three months of continuous consumption, but that minimal histological changes were seen in patients consuming 50 mg of gluten daily. Because these data have not yet been published, these results were not considered further.
Finding 6. The initial approach selected to establish a threshold for gluten, the threshold value selected, and any uncertainty factors that were used to establish the threshold should be reviewed and reconsidered periodically in light of new scientific knowledge and clinical findings.
a. Analytical Methods-Based Approach. As with food allergens, an analytical methods-based approach could be used to establish a threshold for gluten if the available clinical and epidemiological data are insufficient to use one of the other approaches. This approach requires that analytical methods be available to detect all relevant glutens. Thresholds are defined by the limits of detection of the available analytical methods, but there is no relationship between these thresholds and the biological response thresholds. At the time of this report, the lower limits of detection for the commercially available gluten test kits are in the range of 10 µg gluten/g of food, and the ability to robustly quantify samples is in the range of 20 µg gluten/g of food. Establishing thresholds at levels higher than the lower detection limits of the analytical methods requires the use of assumptions about the biological response thresholds. In that case, the thresholds are actually based on using one of the other three approaches and should not be considered an analytical methods-based threshold.
Advantages. A threshold established using the analytical methods-based approach can easily be incorporated into any applicable FDA compliance programs that combine a specific standard method with a standardized sampling scheme.
Limitations. Several factors limit the applicability of the analytical methods-based approach to establish a threshold for gluten. At this time, only one commercially available analytical method has been AOAC validated, and that method was validated for detection at a relatively high concentration of gluten. In addition, there are limited data on the performance of the available methods in the wide variety of food matrices that could potentially contain gluten. Therefore, further characterization of available methods would be necessary before an analytical methods-based threshold could be established. Appropriate methods would need to be developed for the detection of oat gluten.
Finding 7. The analytical methods-based approach could be used to establish a threshold for gluten. However, if this approach is used, the threshold should be replaced by a threshold established using another approach as quickly as possible.
b. Safety Assessment-Based Approach. The safety assessment-based approach could be used to establish a threshold for gluten based on NOAELs or LOAELs reported in the literature in combination with appropriate uncertainty factors. Clinical data in the literature are limited, but a few studies are available that meet the Threshold Working Group's data quality criteria. The currently available clinical studies do not report NOAELs. However, studies are available that could be used to establish a LOAEL from which a threshold could be derived.
Advantages. Establishing a threshold based on NOAELs or LOAELs and the application of appropriate uncertainty factors to estimated exposure levels is fairly straightforward. When there are limited data in the literature, the application of appropriate uncertainty factors can provide confidence that the majority of the sensitive populations will be protected. Establishing thresholds using the safety assessment-based approach and currently available clinical data has the advantage of being directly linked to biological effects.
Limitations. The primary limitation of this approach is the dearth of available prospective clinical data and the general lack of information about the impact of chronic low-level consumption of gluten on the emergence of symptomatic disease in individuals with latent or silent celiac disease. At the current time, the size of the combined uncertainty factors needed would be substantial due to the general lack of data; applying large uncertainty factors to the available data could lead to a gluten threshold that is not achievable, as a practical matter, in foods.
We have identified several data gaps for gluten that contribute to current uncertainty about setting gluten thresholds. The critical areas of uncertainty and variability are:
- Intraspecies differences. Safety assessments typically apply a 10-fold uncertainty factor to account for the variability both between individuals and variability in responses for a particular individual.
- Chronic low-level exposure to gluten in "gluten-free " diets. Data, from either prospective studies or long-term clinical trials, are severely limited on the effect of a long-term gluten-free diet on the manifestations of celiac disease.
- Adequacy of clinical trial data. There is uncertainty as to whether 4-week studies, or even 4-month studies, are of sufficient duration to predict the consequences of long-term ingestion of low levels of gluten. There is additional uncertainty as to whether currently available clinical trials include the most sensitive individuals. Accordingly, there is uncertainty as to whether the standard 10-fold uncertainty factor for variability within a species is sufficient to account for potential highly sensitive individuals. Additional uncertainty arises from the fact that the published clinical trials were designed to identify LOAELs rather than NOAELs.
- Other. Additional data gaps have been identified by the Threshold Working Group; however, the working group concluded that uncertainties associated with these factors were not sufficient to warrant additional uncertainty factors. These other data gaps include the following: (1) it is uncertain what percentage of individuals with celiac disease are sensitive to oat gluten and whether the levels to which they are sensitive are equivalent to those observed for wheat; (2) variability in serving sizes and related exposure factors; and (3) the incompletely defined effect of food processing on the levels of gluten tolerated by individuals with celiac disease.
The uncertainty associated with gluten thresholds arises primarily from the limited amount of clinical data. The critical knowledge gap about individuals with celiac disease is whether chronic, low-level exposure to gluten in a gluten-free diet will cause any harm over a lifetime. We are not aware of any prospective clinical trials that have examined the health of individuals with celiac disease on a gluten-free diet for more than a few months. There is uncertainty as to whether data from these short-term clinical trials will accurately predict reactions following chronic, low-level gluten exposure. Conversely, there appears to be only a small degree of uncertainty as to whether the most sensitive celiac disease populations were included in the available clinical trials since most of the participants had evidence of disease.
As discussed in Section III, there may be an oat-sensitive subpopulation. The possible existence of this oat-sensitive subpopulation raises questions related to the definition of "gluten. " Because there are limited clinical data on the sensitivity of this subpopulation of individuals with celiac disease, the uncertainty related to the LOAELs or NOAELs for these individuals is high. Nevertheless, it is unlikely that theses individuals are substantially more sensitive to oat gluten than they are to wheat gluten.
Table IV-10 presents an example of how an overall uncertainty factor could be derived when estimating a threshold for gluten using the safety assessment-based approach. A standard uncertainty factor of 10 might be applied for intraspecies differences in human responses to gluten.
|Intraspecies difference1||10||Standard for intraspecies variability.|
|Extrapolation from LOAEL 2||10||Standard if NOAEL data not available. Supported by clinical trial data.|
|Chronic, low-level gluten exposure3||6||Estimate using data from gluten clinical trials.|
|Overall Uncertainty Factor4 = 600|
1 This includes both between- and within-individual variability.
2 This includes both a factor for converting the LOAEL to a NOAEL and an additional factor for the uncertainty associated with that conversion factor. Preliminary NOAEL data from an unpublished clinical trial (Fasano, 2005 personal communication) support an approximate 10-fold difference between a NOAEL and published LOAELs (Catassi et al., 1993).
3 Estimated by comparing published LOAELs in an acute, single dose exposure (Ciclitira et al., 1984) with repeated exposure over four weeks (Catassi et al., 1993).
4 Uncertainty is likely to decrease as clinical trial data become available.
Finding 8. The safety assessment-based approach is a viable approach to establish a threshold for gluten using currently available LOAEL data for celiac disease. An overall uncertainty factor should be estimated from the data and applied to the LOAEL to establish a threshold for gluten. Any threshold derived from this approach should be reevaluated as new research data become available. Available data are insufficient at the current time to use this approach to establish a threshold for oat gluten for those individuals with celiac disease who may also be sensitive to oats. However, it is likely that a threshold based on wheat gluten would be protective for individuals susceptible to oat gluten.
c. Risk Assessment-Based Approach. There are few data from human clinical trials that can be used to develop a dose-response model for gluten and celiac disease. In addition, limited data are available on exposure; for example, there are limited data on the actual levels of gluten in the diet of individuals on "gluten-free diets" and on the effects of low-level, chronic gluten exposure in individuals with silent or latent celiac disease. These limitations would lead to a very high level of uncertainty associated with models designed to predict the health effects of gluten in the diet. Therefore, a scientifically defensible hazard characterization and exposure assessment are not possible at the current time.
Finding 9. Use of the quantitative risk assessment-based approach to establish a threshold for gluten does not appear to be feasible at the present time. However, considering the benefits that could be gained from using the risk assessment-based approach, priority should be given to establishing a research program to acquire the knowledge and data needed.
d. Statutorily-Derived Approach. The FALCPA does not include requirements or exemptions that could be used to establish a statutorily-derived threshold for gluten. Also, the law does not define the term "gluten-free. " Potentially, a threshold could be established using the international standards currently under review by Codex (Codex Alimentarius Commission, 2003. However, the proposed Codex standards do not appear to be based on either a scientific rationale for a distinction between naturally gluten-free foods and foods processed to be free of gluten, or a systematic evaluation of clinical data related to the effect of gluten on acute or chronic celiac disease etiology. The levels being considered by Codex seem to be based on anecdotal evidence and on the levels of gluten that are presumed to be historically present in foods that have been called "gluten-free."
Finding 10. There appear to be no suitable statutory requirements or exemptions that would serve as the rationale for using for a statutorily-derived approach to establish a threshold for gluten. This approach is not viable.
Although the FALCPA directs FDA to establish a definition for the term "gluten-free" for food labeling, the quantity and quality of the data needed to accomplish this on a scientific basis are severely limited at the current time relative to all three of the potentially viable approaches. This was aptly summarized by the consensus statement published after a conference of experts convened by the National Institutes of Health which noted that "The strict definition of a gluten-free diet remains controversial due to the lack of an accurate method to detect gluten in food products and the lack of scientific evidence for what constitutes a safe amount of gluten ingestion " (NIH, 2004). These experts concluded that additional research is needed to "Define the minimum safe exposure threshold of gluten in the diet relative to celiac disease " (NIH, 2004).
In view of the consensus opinion stated in the NIH report, the Threshold Working Group concluded that Finding 6 should be reemphasized. Any approach used to establish a threshold for gluten to protect consumers with, or susceptible to, celiac disease should be used in an iterative manner and reexamined periodically to consider new knowledge, data, and approaches.
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