Compositions, devices and methods for Attention Deficit Disorder / Attention Deficit Hyperactivity Disorder (ADD / ADHD) Hypersensitivity Testing

Abstract

There remains a need for compositions, devices and methods for food sensitivity testing aimed at identifying and possibly eliminating trigger foods in patients identified with or suspected of having ADD / ADHD. [Solution] Contemplated test kits, diagnostic devices, and diagnostic methods for food hypersensitivity are based on a rational selection of food preparations with established discriminatory p-values. Kits and diagnostic devices include kits and diagnostic devices with a minimum number of food preparations, wherein the minimum number of food preparations have an average discriminatory p-value of 0.07 or less as determined by their raw p-values, or an average discriminatory p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In a further contemplated aspect, the compositions and methods for food hypersensitivity are also stratified by gender to further enhance predictive value.

Description

[Technical field]

[0001] This application claims priority to U.S. Provisional Patent Application No. 62 / 434,957, filed December 15, 2016, which is incorporated by reference in its entirety.

[0002] The field of the invention relates to the identification of food items that induce and / or exacerbate ADD / ADHD, and in particular to the testing, identification and possible elimination of select food items as trigger foods in patients diagnosed with or suspected of having ADD / ADHD. [Background technology]

[0003] The background discussion includes information that may be useful in understanding the present invention. This information is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.

[0004] Food sensitivities often present with significant problems with attention and / or hyperactivity, especially with respect to ADD / ADHD, a neurodevelopmental psychiatric disorder, the underlying causes of which are not fully understood by the medical community. Most typically, ADD / ADHD is diagnosed through an evaluation of a person's childhood behavior and mental development. Unfortunately, treatments for ADD / ADHD are often ineffective, and new problems can arise due to neurochemical modification. Elimination of one or more food items has shown promise in at least reducing the incidence and / or severity of symptoms. However, ADD / ADHD is often highly variable with respect to food items that trigger symptoms, and no standardized tests are known to help identify trigger food items with a reasonable degree of certainty, so such patients are often left to a trial-and-error approach.

[0005] All publications identified in this specification are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. In the event that a definition or use of a term in an incorporated reference conflicts or is contrary to the definition of that term provided herein, the definition of that term provided herein shall apply and the definition of that term in the reference shall not apply. Summary of the Invention [Problem to be solved by the invention]

[0006] Thus, there remains a need for compositions, devices and methods for food sensitivity testing, particularly to identify and possibly eliminate trigger foods in patients identified with or suspected of having ADD / ADHD. [Means for solving the problem]

[0007] The subject matter of the present invention provides systems and methods for identifying food items that induce and / or exacerbate ADD / ADHD symptoms in diagnosed or suspected ADD / ADHD patients, or that, when ruled out, alleviate ADD / ADHD symptoms. One aspect of the present invention is a test kit for identifying food items that induce and / or exacerbate ADD / ADHD symptoms in diagnosed or suspected ADD / ADHD patients, or that, when ruled out, alleviate ADD / ADHD symptoms. The test kit includes a plurality of different food preparations separately bound to individually addressable solid supports. The plurality of different food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In some embodiments, the mean discrimination p-value is determined by a process comprising comparing assay values ​​of a first patient test cohort population diagnosed with ADD / ADHD or suspected of ADD / ADHD to assay values ​​of a second patient test cohort population not diagnosed with ADHD or suspected of ADD / ADHD.

[0008] Another aspect of the embodiments described herein includes a method of identifying food items that induce or exacerbate, or both, ADD / ADHD symptoms in a patient diagnosed with or suspected of ADD / ADHD, or that, when ruled out, alleviate ADD / ADHD symptoms. The method includes contacting a food preparation with a bodily fluid of a patient diagnosed with or suspected of ADD / ADHD, the bodily fluid being associated with a gender identification. In certain embodiments, the contacting step is performed under conditions that allow IgG from the bodily fluid to bind to at least one component of the food preparation. The method continues with measuring the IgG bound to the at least one component of the food preparation to obtain a signal, and then comparing the signal to a gender-stratified reference value for the food preparation using the gender identification to obtain a result. The method then also includes updating or generating a report using the result.

[0009] Another aspect of the embodiments described herein includes a method of creating a test to identify food items that induce or exacerbate ADD / ADHD symptoms, or both, or that, when ruled out, alleviate ADD / ADHD symptoms in diagnosed or suspected ADD / ADHD patients. The method includes obtaining test results for a plurality of different food preparations. The test results are based on bodily fluids of diagnosed or suspected ADD / ADHD patients and bodily fluids of undiagnosed or unsuspected ADD / ADHD control groups. The method also includes stratifying the test results by gender for each of the different food preparations. The method then continues with assigning different cutoff values ​​for male and female patients for each of the different food preparations for a given percentile ranking.

[0010] Yet another aspect of the embodiments described herein includes the use of a plurality of different food preparations separately bound to individually addressable solid supports in the diagnosis of ADD / ADHD, the plurality of different food preparations being selected based on their average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity adjusted p-values.

[0011] One aspect of the invention relates to a test kit for testing food hypersensitivity in patients diagnosed with or suspected of ADD / ADHD, comprising one or more different food preparations, each food preparation separately bound to an individually addressable solid phase support, the different food preparations having an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In some embodiments, the average discrimination p-value is determined by a process comprising comparing the assay values ​​of a first patient test cohort population diagnosed with ADD / ADHD or suspected of ADD / ADHD to the assay values ​​of a second patient test cohort population not diagnosed with ADD / ADHD or not suspected of ADD / ADHD. In certain embodiments, the one or more different food preparations include at least two food preparations prepared from food items in Table 1, or at least two food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least three food preparations prepared from food items in Table 1, or at least three food preparations selected from foods 1-37 in Table 2. In other embodiments, the one or more different food preparations include at least four food preparations prepared from food items in Table 1, or at least four food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least five food preparations prepared from food items in Table 1, or at least five food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least six food preparations prepared from food items in Table 1, or at least six food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least seven food preparations prepared from food items in Table 1, or at least seven food preparations selected from foods 1-37 in Table 2.In yet another embodiment, the one or more different food preparations include at least eight food preparations prepared from food items in Table 1, or at least eight food preparations selected from foods 1-37 in Table 2. In a particular embodiment, the one or more different food preparations include at least nine food preparations prepared from food items in Table 1, or at least nine food preparations selected from foods 1-37 in Table 2. In a particular embodiment, the one or more different food preparations include at least ten food preparations prepared from food items in Table 1, or at least ten food preparations selected from foods 1-37 in Table 2. In a particular embodiment, the one or more different food preparations include at least eleven food preparations prepared from food items in Table 1, or at least eleven food preparations selected from foods 1-37 in Table 2. In yet another embodiment, the one or more different food preparations include at least twelve food preparations prepared from food items in Table 1, or at least twelve food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least 13 food preparations prepared from food items in Table 1, or at least 13 food preparations selected from foods 1-37 in Table 2. In certain embodiments, the one or more different food preparations include at least 14 food preparations prepared from food items in Table 1, or at least 14 food preparations selected from foods 1-37 in Table 2.

[0012] In some embodiments, the one or more food preparations are at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least eight food preparations selected from foods 1-37 of Table 2, at least one food preparation ... at least 9 food preparations selected from Foods 1 to 37 of Table 2, at least 10 food preparations selected from Foods 1 to 37 of Table 2, at least 11 food preparations selected from Foods 1 to 37 of Table 2, at least 12 food preparations selected from Foods 1 to 37 of Table 2, at least 13 food preparations selected from Foods 1 to 37 of Table 2, at least 14 food preparations selected from Foods 1 to 37 of Table 2, at least 15 food preparations selected from Foods 1 to 37 of Table 2, at least 16 food preparations selected from Foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2, at least 32 food preparations selected from foods 1 to 37 of Table 2,At least 33 food preparations selected from Foods 1 to 37 in Table 2, at least 34 food preparations selected from Foods 1 to 37 in Table 2, at least 35 food preparations selected from Foods 1 to 37 in Table 2, at least 36 food preparations selected from Foods 1 to 37 in Table 2, and at least 37 food preparations selected from Foods 1 to 37 in Table 2.

[0013] In some embodiments of the invention, the one or more different food preparations are at least one food preparation selected from foods 1-37 of Table 2, at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least one food preparation ... at least 8 food preparations selected from foods 1 to 37 of Table 2, at least 9 food preparations selected from foods 1 to 37 of Table 2, at least 10 food preparations selected from foods 1 to 37 of Table 2, at least 11 food preparations selected from foods 1 to 37 of Table 2, at least 12 food preparations selected from foods 1 to 37 of Table 2, at least 13 food preparations selected from foods 1 to 37 of Table 2, at least 14 food preparations selected from foods 1 to 37 of Table 2, at least 15 food preparations selected from foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2,Selected from the group consisting of at least 32 food preparations selected from foods 1 to 37 of Table 2, at least 33 food preparations selected from foods 1 to 37 of Table 2, at least 34 food preparations selected from foods 1 to 37 of Table 2, at least 35 food preparations selected from foods 1 to 37 of Table 2, at least 36 food preparations selected from foods 1 to 37 of Table 2, and at least 37 food preparations selected from foods 1 to 37 of Table 2. In other embodiments, the one or more different food preparations are selected from the group consisting of cantaloupe (melon), wheat, tomato, cucumber, pumpkin, almond, egg, cauliflower, pinto beans, broccoli, orange, butter, corn, lettuce, rye, peach, green peas, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olives, cottage cheese, grapefruit, black walnuts, milk, soybean, and chili pepper.

[0014] In other embodiments of the invention, the one or more different food preparations have an average discrimination p-value of 0.05 or less as determined by raw p-values, or an average discrimination p-value of 0.08 or less as determined by FDR multiplicity-adjusted p-values, hi other embodiments, the one or more different food preparations have an average discrimination p-value of 0.025 or less as determined by raw p-values, or an average discrimination p-value of 0.07 or less as determined by FDR multiplicity-adjusted p-values.

[0015] In another embodiment of the invention, the FDR multiplicity-adjusted p-value is adjusted for at least one of age and sex, hi another embodiment, the FDR multiplicity-adjusted p-value is adjusted for age and sex.

[0016] In another embodiment of the invention, when adjusted for a single gender, at least 50% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In another embodiment, when adjusted for a single gender, at least 55% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 60% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 65% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 70% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In another embodiment, when adjusted for a single gender, at least 75% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 80% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.

[0017] In other embodiments, when adjusted for a single gender, at least 85% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 95% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 95% of the one or more different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, all of the one or more distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.

[0018] In certain embodiments of the invention, the one or more different food preparations are crude filtered aqueous extracts. In other embodiments, the one or more different food preparations are processed aqueous extracts. In yet other embodiments, the one or more different food preparations are crude filtered aqueous extracts or processed aqueous extracts. In other certain embodiments, the one or more different food preparations are crude filtered aqueous extracts or processed aqueous extracts.

[0019] In certain embodiments of the invention, the solid support is a well of a multi-well plate, a bead, an electrical sensor, a chemical sensor, a microchip or an absorbent film.

[0020] In another specific embodiment, the present invention relates to a method for testing food sensitivity in a patient diagnosed with or suspected of ADD / ADHD, comprising contacting a test kit (or diagnostic device) of the present invention with a body fluid of a patient diagnosed with or suspected of ADD / ADHD, performing the contacting step under conditions that allow IgG from the body fluid to bind to at least one component of the food preparation, measuring the IgG bound to the at least one component of the food preparation to obtain a signal, and updating or generating a report using the signal. In some embodiments, the body fluid of the patient is selected from the group consisting of whole blood, plasma, serum, saliva, urine, and a stool suspension. In other embodiments, the contacting step of the test kit is performed with a plurality of different food preparations.

[0021] In certain embodiments, the plurality of different food preparations are prepared from food items in Table 1 or selected from foods 1-37 in Table 2. In yet other embodiments, the plurality of different food preparations are at least one food preparation selected from foods 1-37 in Table 2, at least two food preparations selected from foods 1-37 in Table 2, at least three food preparations selected from foods 1-37 in Table 2, at least four food preparations selected from foods 1-37 in Table 2, at least five food preparations selected from foods 1-37 in Table 2, at least six food preparations ... at least seven food preparations selected from foods 1 to 37 of Table 2, at least eight food preparations selected from foods 1 to 37 of Table 2, at least nine food preparations selected from foods 1 to 37 of Table 2, at least ten food preparations selected from foods 1 to 37 of Table 2, at least eleven food preparations selected from foods 1 to 37 of Table 2, at least twelve food preparations selected from foods 1 to 37 of Table 2, at least thirteen food preparations selected from foods 1 to 37 of Table 2, at least four ... one food preparation selected from foods 1 to 37 of Table 2, at least 15 food preparations selected from foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2,At least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2, at least 32 food preparations selected from foods 1 to 37 of Table 2, at least 33 food preparations selected from foods 1 to 37 of Table 2, at least 34 food preparations selected from foods 1 to 37 of Table 2, at least 35 food preparations selected from foods 1 to 37 of Table 2, at least 36 food preparations selected from foods 1 to 37 of Table 2, and at least 37 food preparations selected from foods 1 to 37 of Table 2.

[0022] In other embodiments, the different food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, the different food preparations have an average discrimination p-value of 0.05 or less as determined by raw p-values, or an average discrimination p-value of 0.08 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, the different food preparations have an average discrimination p-value of 0.025 or less as determined by raw p-values, or an average discrimination p-value of 0.07 or less as determined by FDR multiplicity-adjusted p-values. In certain embodiments, the different food preparations all have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values.

[0023] In some embodiments, the food preparation is immobilized on a solid surface. In other embodiments, the food preparation is immobilized on a solid surface, optionally in an addressable manner.

[0024] In yet another embodiment, the step of measuring IgG bound to the at least one component of the food preparation is performed by an immunoassay test.In yet another embodiment, the method comprises using the gender identification to compare the signal to a gender-stratified reference value for the food preparation to obtain a result, wherein the gender-stratified reference value for the food preparation is at least a 90th percentile value.

[0025] In another aspect, the present invention relates to a method for generating a food sensitivity test for diagnosed or suspected ADD / ADHD patients, the method comprising the steps of obtaining test results for a plurality of different food preparations, the test results being based on body fluids of diagnosed or suspected ADD / ADHD patients and of a control group not diagnosed with or not suspected of ADD / ADHD; stratifying the test results by gender for each of the different food preparations; assigning different cut-off values ​​for male and female patients for each of the different food preparations for a given percentile ranking; selecting a plurality of different food preparations, each of which has a discriminatory p-value of 0.07 or less as determined by a raw p-value or a discriminatory p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value; and generating a test for food sensitivity in diagnosed or suspected ADD / ADHD patients consisting essentially of the selected food preparations.

[0026] In some embodiments, the test results are ELISA results.

[0027] In other embodiments, the plurality of different food preparations comprises at least two food preparations prepared from food items in Table 1, or at least two food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least three food preparations prepared from food items in Table 1, or at least three food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least four food preparations prepared from food items in Table 1, or at least four food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least five food preparations prepared from food items in Table 1, or at least five food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least six food preparations prepared from food items in Table 1, or at least six food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least seven food preparations prepared from food items in Table 1, or at least seven food preparations selected from foods 1-37 in Table 2. In yet another embodiment, the plurality of different food preparations comprises at least eight food preparations prepared from food items in Table 1, or at least eight food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least nine food preparations prepared from food items in Table 1, or at least nine food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least ten food preparations prepared from food items in Table 1, or at least ten food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least eleven food preparations prepared from food items in Table 1, or at least eleven food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 12 food preparations prepared from food items in Table 1, or at least 12 food preparations selected from foods 1-37 in Table 2.In another embodiment, the plurality of different food preparations comprises at least 13 food preparations prepared from food items in Table 1, or at least 13 food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 14 food preparations prepared from food items in Table 1, or at least 14 food preparations selected from foods 1-37 in Table 2.

[0028] In another embodiment, the plurality of different food preparations comprises at least one food preparation selected from foods 1-37 of Table 2, at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven ... at least 8 food preparations selected from Foods 1 to 37 of Table 2, at least 9 food preparations selected from Foods 1 to 37 of Table 2, at least 10 food preparations selected from Foods 1 to 37 of Table 2, at least 11 food preparations selected from Foods 1 to 37 of Table 2, at least 12 food preparations selected from Foods 1 to 37 of Table 2, at least 13 food preparations selected from Foods 1 to 37 of Table 2, at least 14 food preparations selected from Foods 1 to 37 of Table 2, at least 15 food preparations selected from Foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, At least 24 food preparations selected from foods 1 to 37, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2,At least 32 food preparations selected from foods 1-37 of Table 2, at least 33 food preparations selected from foods 1-37 of Table 2, at least 34 food preparations selected from foods 1-37 of Table 2, at least 35 food preparations selected from foods 1-37 of Table 2, at least 36 food preparations selected from foods 1-37 of Table 2, and at least 37 food preparations selected from foods 1-37 of Table 2. In yet another embodiment, the different food preparations are selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soy, and chili pepper. ,

[0029] In other embodiments, the different food preparations have an average discrimination p-value of 0.05 or less as determined by raw p-values, or an average discrimination p-value of 0.08 or less as determined by FDR multiplicity-adjusted p-values, hi another embodiment, the different food preparations have an average discrimination p-value of 0.025 or less as determined by raw p-values, or an average discrimination p-value of 0.07 or less as determined by FDR multiplicity-adjusted p-values.

[0030] In certain embodiments, said bodily fluid of said patient is selected from the group consisting of whole blood, plasma, serum, saliva, urine and a fecal suspension.

[0031] In other embodiments, the predetermined percentile rank is at least the 90th percentile.

[0032] In yet another embodiment, the cut-off values ​​for male and female patients have a difference of at least 10% (absolute value).

[0033] In yet another embodiment, the method further comprises normalizing the results to the patient's total IgG, hi another embodiment, the method further comprises normalizing the results to the overall mean food-specific IgG result for the patient.

[0034] In another embodiment, the method further comprises identifying a subset of patients whose susceptibility to the food preparations underlies ADD / ADHD by a raw p-value or an average discrimination p-value of 0.01 or less. In another embodiment, the method further comprises determining a number of the food preparations that can be used to confirm ADD / ADHD by a raw p-value or an average discrimination p-value of 0.01 or less.

[0035] In a particular aspect, the present invention relates to the use of a plurality of different food preparations separately bound to individually addressable solid supports in the diagnosis of ADD / ADHD, said plurality of different food preparations having an average discrimination p-value of 0.07 or less as determined by a raw p-value, or having an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In a particular embodiment, said plurality of food preparations comprises at least two food preparations prepared from food items in Table 1, or at least two food preparations selected from foods 1-37 in Table 2. In another embodiment, said plurality of different food preparations comprises at least three food preparations prepared from food items in Table 1, or at least three food preparations selected from foods 1-37 in Table 2. In another embodiment, said plurality of different food preparations comprises at least four food preparations prepared from food items in Table 1, or at least four food preparations selected from foods 1-37 in Table 2.

[0036] In certain embodiments, the plurality of different food preparations comprises at least five food preparations prepared from food items in Table 1, or at least five food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least six food preparations prepared from food items in Table 1, or at least six food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least seven food preparations prepared from food items in Table 1, or at least seven food preparations selected from foods 1-37 in Table 2. In yet another embodiment, the plurality of different food preparations comprises at least eight food preparations prepared from food items in Table 1, or at least eight food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least nine food preparations prepared from food items in Table 1, or at least nine food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 10 food preparations prepared from food items in Table 1, or at least 10 food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 11 food preparations prepared from food items in Table 1, or at least 11 food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 12 food preparations prepared from food items in Table 1, or at least 12 food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 13 food preparations prepared from food items in Table 1, or at least 13 food preparations selected from foods 1-37 in Table 2. In another embodiment, the plurality of different food preparations comprises at least 14 food preparations prepared from food items in Table 1, or at least 14 food preparations selected from foods 1-37 in Table 2.

[0037] In other embodiments, the plurality of food preparations comprises at least one food preparation selected from foods 1-37 of Table 2, at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least one food preparation ... at least 8 food preparations selected from foods 1 to 37 of Table 2, at least 9 food preparations selected from foods 1 to 37 of Table 2, at least 10 food preparations selected from foods 1 to 37 of Table 2, at least 11 food preparations selected from foods 1 to 37 of Table 2, at least 12 food preparations selected from foods 1 to 37 of Table 2, at least 13 food preparations selected from foods 1 to 37 of Table 2, at least 14 food preparations selected from foods 1 to 37 of Table 2, at least 15 food preparations selected from foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparation at least 16 food preparations selected from Foods 1 to 37 of Table 2, at least 17 food preparations selected from Foods 1 to 37 of Table 2, at least 18 food preparations selected from Foods 1 to 37 of Table 2, at least 19 food preparations selected from Foods 1 to 37 of Table 2, at least 20 food preparations selected from Foods 1 to 37 of Table 2, at least 21 food preparations selected from Foods 1 to 37 of Table 2, at least 22 food preparations selected from Foods 1 to 37 of Table 2, at least 23 food preparations selected from Foods 1 to 37 of Table 2, at least 24 food preparations selected from Foods 1 to 37 of Table 2, at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2, at least 32 food preparations selected from Foods 1 to 37 of Table 2, at least 33 food preparations selected from Foods 1 to 37 of Table 2, at least 34 food preparations selected from Foods 1 to 37 of Table 2, at least 35 food preparations selected from Foods 1 to 37 of Table 2, at least 36 food preparations selected from Foods 1 to 37 of Table 2, at least 37 food preparations selected from Foods 1 to 37 of Table 2, at least 38 food preparations selected from Foods 1 to 37 of Table 2, at least 39 at least 24 food preparations selected from Foods 1 to 37 of Table 2, at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 29 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2,At least 32 food preparations selected from foods 1-37 of Table 2, at least 33 food preparations selected from foods 1-37 of Table 2, at least 34 food preparations selected from foods 1-37 of Table 2, at least 35 food preparations selected from foods 1-37 of Table 2, at least 36 food preparations selected from foods 1-37 of Table 2, and at least 37 food preparations selected from foods 1-37 of Table 2. In yet another embodiment, the plurality of food preparations is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soy, and chili pepper. ,

[0038] In certain embodiments, the distinct food preparations have an average discrimination p-value of 0.05 or less as determined by raw p-values, or an average discrimination p-value of 0.08 or less as determined by FDR multiplicity-adjusted p-values, hi other embodiments, the distinct food preparations have an average discrimination p-value of 0.025 or less as determined by raw p-values, or an average discrimination p-value of 0.07 or less as determined by FDR multiplicity-adjusted p-values.

[0039] In certain other embodiments, the FDR multiplicity-adjusted p-values ​​are adjusted for at least one of age and sex, hi other embodiments, the FDR multiplicity-adjusted p-values ​​are adjusted for age and sex.

[0040] In other embodiments, when adjusted for a single gender, at least 50% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 55% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 60% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 65% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 70% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 75% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 80% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.In other embodiments, when adjusted for a single gender, at least 85% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 90% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 95% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, all of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity adjusted p-values.

[0041] In another embodiment, the plurality of distinct food preparations is a crude filtered aqueous extract. In another embodiment, the plurality of distinct food preparations is a processed aqueous extract. In yet another embodiment, the plurality of distinct food preparations is a crude filtered aqueous extract or a processed aqueous extract.

[0042] In another embodiment, the solid support is a well of a multi-well plate, a bead, an electrical sensor, a chemical sensor, a microchip, or an absorbent film.

[0043] In other embodiments, the mean discrimination p-value is determined by a process comprising comparing assay values ​​of a first patient test cohort population diagnosed with ADD / ADHD headache or suspected of having ADD / ADHD headache to assay values ​​of a second patient test cohort population not diagnosed with ADHD headache or not suspected of having ADD / ADHD headache.

[0044] In yet another embodiment, the test results are ELISA results obtained from a process comprising contacting each of the different food preparations individually with the bodily fluid of each patient.

[0045] In a particular aspect, the present invention relates to a detection device for food hypersensitivity testing for patients diagnosed with or suspected of ADD / ADHD, the detection device consisting essentially of a plurality of different food preparations, each of which is separately bound to an individually addressable solid phase support, each of which has a discrimination p-value of 0.07 or less as determined by a raw p-value, or a discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In another embodiment, the discrimination p-value is determined by a process comprising comparing the assay value of a first patient testing cohort population diagnosed with ADD / ADHD or suspected of ADD / ADHD with the assay value of a second patient testing cohort population not diagnosed with ADHD or not suspected of ADD / ADHD.

[0046] In some embodiments, the plurality of food preparations comprises at least two food preparations selected from the food items of Table 1, or at least two food preparations selected from foods 1-37 of Table 2. In another embodiment, the plurality of different food preparations comprises at least three food preparations prepared from the food items of Table 1, or at least three food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least four food preparations prepared from the food items of Table 1, or at least four food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least five food preparations prepared from the food items of Table 1, or at least five food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least six food preparations prepared from the food items of Table 1, or at least six food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations includes at least seven food preparations prepared from food items in Table 1, or at least seven food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least eight food preparations prepared from food items in Table 1, or at least eight food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least nine food preparations prepared from food items in Table 1, or at least nine food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least ten food preparations prepared from food items in Table 1, or at least ten food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least eleven food preparations prepared from food items in Table 1, or at least eleven food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations comprises at least 12 food preparations prepared from food items in Table 1, or at least 12 food preparations selected from foods 1-37 in Table 2.In other embodiments, the plurality of different food preparations comprises at least 13 food preparations prepared from food items in Table 1, or at least 13 food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations comprises at least 14 food preparations prepared from food items in Table 1, or at least 14 food preparations selected from foods 1-37 in Table 2.

[0047] In other embodiments, the plurality of food preparations comprises at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least eight ... at least 9 food preparations selected from foods 1 to 37 of Table 2, at least 10 food preparations selected from foods 1 to 37 of Table 2, at least 11 food preparations selected from foods 1 to 37 of Table 2, at least 12 food preparations selected from foods 1 to 37 of Table 2, at least 13 food preparations selected from foods 1 to 37 of Table 2, at least 14 food preparations selected from foods 1 to 37 of Table 2, at least 15 food preparations selected from foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2, at least 32 food at least 17 food preparations selected from Foods 1 to 37 of Table 2, at least 18 food preparations selected from Foods 1 to 37 of Table 2, at least 19 food preparations selected from Foods 1 to 37 of Table 2, at least 20 food preparations selected from Foods 1 to 37 of Table 2, at least 21 food preparations selected from Foods 1 to 37 of Table 2, at least 22 food preparations selected from Foods 1 to 37 of Table 2, at least 23 food preparations selected from Foods 1 to 37 of Table 2, at least 24 food preparations selected from Foods 1 to 37 of Table 2, at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2, at least 32 food preparations selected from Foods 1 to 37 of Table 2, at least 33 food preparations selected from Foods 1 to 37 of Table 2, at least 34 food preparations selected from Foods 1 to 37 of Table 2, at least 35 food preparations selected from Foods 1 to 37 of Table 2, at least 36 food preparations selected from Foods 1 to 37 of Table 2, at least 37 food preparations selected from Foods 1 to 37 of Table 2, at least 38 food preparations selected from Foods 1 to 37 of Table 2, at least 39 food preparations selected from Foods 1 to 37 of Table 2, at least 40 at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 29 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2, at least 32 food preparations selected from Foods 1 to 37 of Table 2,At least 33 food preparations selected from foods 1-37 of Table 2, at least 34 food preparations selected from foods 1-37 of Table 2, at least 35 food preparations selected from foods 1-37 of Table 2, at least 36 food preparations selected from foods 1-37 of Table 2, and at least 37 food preparations selected from foods 1-37 of Table 2. In yet another embodiment, the plurality of food preparations is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0048] In some embodiments, the distinct plurality of food preparations consists essentially of food preparations each having a discriminatory p-value of 0.05 or less as determined by a raw p-value, or a discriminatory p-value of 0.08 or less as determined by an FDR multiplicity-adjusted p-value.

[0049] In other embodiments, the FDR multiplicity-adjusted p-value is adjusted for at least one of age and sex.

[0050] In other embodiments, when adjusted for a single gender, at least 50% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 55% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 60% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 65% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 70% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 75% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 80% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.In yet other embodiments, when adjusted for a single gender, at least 85% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 90% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 95% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values.

[0051] In other embodiments, the plurality of distinct food preparations are crude filtered aqueous extracts. In other embodiments, the plurality of distinct food preparations are processed aqueous extracts. In other embodiments, the plurality of distinct food preparations are crude filtered aqueous extracts or processed aqueous extracts.

[0052] In certain aspects, the present invention relates to a detection device for food hypersensitivity testing for patients diagnosed with or suspected of ADD / ADHD, the detection device consisting essentially of a plurality of different food preparations, each food preparation separately bound to an individually addressable solid phase support, the plurality of different food preparations having an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In some embodiments, the average discrimination p-value is determined by a process comprising comparing the assay values ​​of a first patient testing cohort population diagnosed with ADD / ADHD or suspected of ADD / ADHD with the assay values ​​of a second patient testing cohort population not diagnosed with ADHD or suspected of ADD / ADHD.

[0053] In other embodiments, the plurality of food preparations comprises at least two food preparations selected from the food items of Table 1, or at least two food preparations selected from foods 1-37 of Table 2. In another embodiment, the plurality of different food preparations comprises at least three food preparations prepared from the food items of Table 1, or at least three food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least four food preparations prepared from the food items of Table 1, or at least four food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least five food preparations prepared from the food items of Table 1, or at least five food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations comprises at least six food preparations prepared from the food items of Table 1, or at least six food preparations selected from foods 1-37 of Table 2. In other embodiments, the plurality of different food preparations includes at least seven food preparations prepared from food items in Table 1, or at least seven food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least eight food preparations prepared from food items in Table 1, or at least eight food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least nine food preparations prepared from food items in Table 1, or at least nine food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least ten food preparations prepared from food items in Table 1, or at least ten food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations includes at least eleven food preparations prepared from food items in Table 1, or at least eleven food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations comprises at least 12 food preparations prepared from food items in Table 1, or at least 12 food preparations selected from foods 1-37 in Table 2.In other embodiments, the plurality of different food preparations comprises at least 13 food preparations prepared from food items in Table 1, or at least 13 food preparations selected from foods 1-37 in Table 2. In other embodiments, the plurality of different food preparations comprises at least 14 food preparations prepared from food items in Table 1, or at least 14 food preparations selected from foods 1-37 in Table 2.

[0054] In other embodiments, the plurality of food preparations comprises at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least eight ... at least 9 food preparations selected from foods 1 to 37 of Table 2, at least 10 food preparations selected from foods 1 to 37 of Table 2, at least 11 food preparations selected from foods 1 to 37 of Table 2, at least 12 food preparations selected from foods 1 to 37 of Table 2, at least 13 food preparations selected from foods 1 to 37 of Table 2, at least 14 food preparations selected from foods 1 to 37 of Table 2, at least 15 food preparations selected from foods 1 to 37 of Table 2, at least 16 food preparations selected from foods 1 to 37 of Table 2, at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37 of Table 2, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2, at least 32 food at least 17 food preparations selected from Foods 1 to 37 of Table 2, at least 18 food preparations selected from Foods 1 to 37 of Table 2, at least 19 food preparations selected from Foods 1 to 37 of Table 2, at least 20 food preparations selected from Foods 1 to 37 of Table 2, at least 21 food preparations selected from Foods 1 to 37 of Table 2, at least 22 food preparations selected from Foods 1 to 37 of Table 2, at least 23 food preparations selected from Foods 1 to 37 of Table 2, at least 24 food preparations selected from Foods 1 to 37 of Table 2, at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2, at least 32 food preparations selected from Foods 1 to 37 of Table 2, at least 33 food preparations selected from Foods 1 to 37 of Table 2, at least 34 food preparations selected from Foods 1 to 37 of Table 2, at least 35 food preparations selected from Foods 1 to 37 of Table 2, at least 36 food preparations selected from Foods 1 to 37 of Table 2, at least 37 food preparations selected from Foods 1 to 37 of Table 2, at least 38 food preparations selected from Foods 1 to 37 of Table 2, at least 39 food preparations selected from Foods 1 to 37 of Table 2, at least 40 at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 29 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food preparations selected from Foods 1 to 37 of Table 2, at least 32 food preparations selected from Foods 1 to 37 of Table 2,At least 33 food preparations selected from foods 1-37 of Table 2, at least 34 food preparations selected from foods 1-37 of Table 2, at least 35 food preparations selected from foods 1-37 of Table 2, at least 36 food preparations selected from foods 1-37 of Table 2, and at least 37 food preparations selected from foods 1-37 of Table 2. In yet another embodiment, the plurality of food preparations is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0055] In certain other embodiments, the distinct plurality of food preparations consists essentially of food preparations having an average discrimination p-value of 0.05 or less as determined by a raw p-value, or an average discrimination p-value of 0.08 or less as determined by an FDR multiplicity-adjusted p-value.

[0056] In yet other embodiments, the FDR multiplicity-adjusted p-value is adjusted for at least one of age and sex.

[0057] In yet another embodiment, when adjusted for a single gender, at least 50% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 55% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In another embodiment, when adjusted for a single gender, at least 60% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 65% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, when adjusted for a single gender, at least 70% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 75% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In certain embodiments, when adjusted for a single gender, at least 80% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.In another embodiment, when adjusted for a single gender, at least 85% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.

[0058] In yet another embodiment, the plurality of different food preparations are crude aqueous extracts. In another embodiment, the plurality of different food preparations are processed aqueous extracts. In yet another embodiment, the plurality of different food preparations are crude aqueous extracts or processed aqueous extracts.

[0059] In a particular aspect, the present invention relates to a detection device for food hypersensitivity testing for patients diagnosed with or suspected of having ADD / ADHD, comprising a plurality of different food preparations, each food preparation being separately bound to an individually addressable solid phase support, and at least 50% of the plurality of different food preparations each having a discrimination p-value of 0.07 or less as determined by a raw p-value, or a discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.

[0060] In one embodiment, at least 50% of the distinct food preparations each have a discrimination p-value of 0.07 or less when determined by raw p-values, or a discrimination p-value of 0.10 or less when determined by FDR multiplicity-adjusted p-values. In another embodiment, at least 55% of the distinct food preparations each have a discrimination p-value of 0.07 or less when determined by raw p-values, or a discrimination p-value of 0.10 or less when determined by FDR multiplicity-adjusted p-values. In yet another embodiment, at least 60% of the distinct food preparations each have a discrimination p-value of 0.07 or less when determined by raw p-values, or a discrimination p-value of 0.10 or less when determined by FDR multiplicity-adjusted p-values. In another embodiment, at least 65% of the distinct food preparations each have a discrimination p-value of 0.07 or less when determined by raw p-values, or a discrimination p-value of 0.10 or less when determined by FDR multiplicity-adjusted p-values. In another embodiment, at least 70% of the different food preparations have a discrimination p-value of 0.07 or less, respectively, as determined by raw p-values, or a discrimination p-value of 0.10 or less, respectively, as determined by FDR multiplicity-adjusted p-values. In another embodiment, at least 75% of the different food preparations have a discrimination p-value of 0.07 or less, respectively, as determined by raw p-values, or a discrimination p-value of 0.10 or less, respectively, as determined by FDR multiplicity-adjusted p-values. In a particular embodiment, at least 80% of the different food preparations have a discrimination p-value of 0.07 or less, respectively, as determined by raw p-values, or a discrimination p-value of 0.10 or less, respectively, as determined by FDR multiplicity-adjusted p-values. In another embodiment, at least 85% of the different food preparations have a discrimination p-value of 0.07 or less, respectively, as determined by raw p-values, or a discrimination p-value of 0.10 or less, respectively, as determined by FDR multiplicity-adjusted p-values.In other embodiments, at least 90% of the distinct food preparations each have a discrimination p-value of 0.07 or less as determined by raw p-values, or a discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, at least 95% of the distinct food preparations each have a discrimination p-value of 0.07 or less as determined by raw p-values, or a discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values.

[0061] In some embodiments, the plurality of food preparations comprises at least two food preparations selected from foods 1-37 of Table 2, at least three food preparations selected from foods 1-37 of Table 2, at least four food preparations selected from foods 1-37 of Table 2, at least five food preparations selected from foods 1-37 of Table 2, at least six food preparations selected from foods 1-37 of Table 2, at least seven food preparations selected from foods 1-37 of Table 2, at least eight ... at least 9 food preparations selected from Foods 1 to 37 of Table 2, at least 10 food preparations selected from Foods 1 to 37 of Table 2, at least 11 food preparations selected from Foods 1 to 37 of Table 2, at least 12 food preparations selected from Foods 1 to 37 of Table 2, at least 13 food preparations selected from Foods 1 to 37 of Table 2, at least 14 food preparations selected from Foods 1 to 37 of Table 2, at least 15 food preparations selected from Foods 1 to 37 of Table 2, at least 16 food preparations selected from Foods 1 to 37 of Table 2, at least 17 food preparations selected from Foods 1 to 37 of Table 2, at least 18 food preparations selected from Foods 1 to 37 of Table 2, at least 19 food preparations selected from Foods 1 to 37 of Table 2, at least 20 food preparations selected from Foods 1 to 37 of Table 2, at least 21 food preparations selected from Foods 1 to 37 of Table 2, at least 22 food preparations selected from Foods 1 to 37 of Table 2, at least 23 food preparations selected from Foods 1 to 37 of Table 2, at least 24 food preparations selected from Foods 1 to 37 of Table 2, at least 25 food preparations selected from Foods 1 to 37 of Table 2, at least 26 food preparations selected from Foods 1 to 37 of Table 2, at least 27 food preparations selected from Foods 1 to 37 of Table 2, at least 28 food preparations selected from Foods 1 to 37 of Table 2, at least 29 food preparations selected from Foods 1 to 37 of Table 2, at least 30 food preparations selected from Foods 1 to 37 of Table 2, at least 31 food at least 17 food preparations selected from foods 1 to 37 of Table 2, at least 18 food preparations selected from foods 1 to 37 of Table 2, at least 19 food preparations selected from foods 1 to 37 of Table 2, at least 20 food preparations selected from foods 1 to 37 of Table 2, at least 21 food preparations selected from foods 1 to 37 of Table 2, at least 22 food preparations selected from foods 1 to 37 of Table 2, at least 23 food preparations selected from foods 1 to 37 of Table 2, at least 24 food preparations selected from foods 1 to 37 of Table 2, at least 25 food preparations selected from foods 1 to 37, at least 26 food preparations selected from foods 1 to 37 of Table 2, at least 27 food preparations selected from foods 1 to 37 of Table 2, at least 28 food preparations selected from foods 1 to 37 of Table 2, at least 29 food preparations selected from foods 1 to 37 of Table 2, at least 30 food preparations selected from foods 1 to 37 of Table 2, at least 31 food preparations selected from foods 1 to 37 of Table 2, at least 32 food preparations selected from foods 1 to 37 of Table 2,At least 33 food preparations selected from Foods 1 to 37 in Table 2, at least 34 food preparations selected from Foods 1 to 37 in Table 2, at least 35 food preparations selected from Foods 1 to 37 in Table 2, at least 36 food preparations selected from Foods 1 to 37 in Table 2, and at least 37 food preparations selected from Foods 1 to 37 in Table 2.

[0062] In some embodiments, the different food preparations have an average discrimination p-value of 0.05 or less as determined by a raw p-value, or an average discrimination p-value of 0.08 or less as determined by an FDR multiplicity-adjusted p-value.

[0063] In other embodiments, the FDR multiplicity-adjusted p-value is adjusted for at least one of age and sex.

[0064] In yet another embodiment, when adjusted for a single gender, at least 50% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In another embodiment, when adjusted for a single gender, at least 55% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 60% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In another embodiment, when adjusted for a single gender, at least 65% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 70% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet another embodiment, when adjusted for a single gender, at least 75% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 80% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value.In yet other embodiments, when adjusted for a single gender, at least 85% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 90% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values. In yet other embodiments, when adjusted for a single gender, at least 95% of the distinct food preparations have an average discrimination p-value of 0.07 or less as determined by raw p-values, or an average discrimination p-value of 0.10 or less as determined by FDR multiplicity-adjusted p-values.

[0065] In some embodiments, the different food preparations are crude aqueous extracts. In other embodiments, the different food preparations are processed aqueous extracts. In yet other embodiments, the different food preparations are crude aqueous extracts or processed aqueous extracts.

[0066] In a particular aspect, the present invention relates to a detection device for food hypersensitivity testing on a biological sample derived from a patient diagnosed with or suspected of having ADD / ADHD, the detection device comprising a solid surface with a plurality of food preparations, each food preparation being individually bound to said solid surface, the plurality of food preparations consisting essentially of ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In certain embodiments, the inducer foods are at least two food items selected from foods 1-37 of Table 2, at least three food items selected from foods 1-37 of Table 2, at least four food items selected from foods 1-37 of Table 2, at least five food items selected from foods 1-37 of Table 2, at least six food items selected from foods 1-37 of Table 2, at least seven food items selected from foods 1-37 of Table 2, at least eight food items selected from foods 1-37 of Table 2, at least nine food items selected from foods 1-37 of Table 2, at least ten food items selected from foods 1-37 of Table 2, at least eleven food items selected from foods 1-37 of Table 2, at least twelve food items selected from foods 1-37 of Table 2, at least thirteen food items selected from foods 1-37 of Table 2, at least four ... at least 15 food items selected from foods 1-37 of Table 2, at least 16 food items selected from foods 1-37 of Table 2, at least 17 food items selected from foods 1-37 of Table 2, at least 18 food items selected from foods 1-37 of Table 2, at least 19 food items selected from foods 1-37 of Table 2, at least 20 food items selected from foods 1-37 of Table 2, at least 21 food items selected from foods 1-37 of Table 2, at least 22 food items selected from foods 1-37 of Table 2, at least 23 food items selected from foods 1-37 of Table 2, at least 24 food items selected from foods 1-37 of Table 2, at least 25 food items selected from foods 1-37 of Table 2, at least 26 food items selected from foods 1-37 of Table 2, at least 27 food items selected from foods 1-37 of Table 2,Selected from the group consisting of at least 28 food items selected from foods 1 to 37 of Table 2, at least 29 food items selected from foods 1 to 37 of Table 2, at least 30 food items selected from foods 1 to 37 of Table 2, at least 31 food items selected from foods 1 to 37 of Table 2, at least 32 food items selected from foods 1 to 37 of Table 2, at least 33 food items selected from foods 1 to 37 of Table 2, at least 34 food items selected from foods 1 to 37 of Table 2, at least 35 food items selected from foods 1 to 37 of Table 2, at least 36 food items selected from foods 1 to 37 of Table 2, and at least 37 food items selected from foods 1 to 37 of Table 2. In other embodiments, the trigger food is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almonds, eggs, cauliflower, pinto beans, broccoli, oranges, butter, corn, lettuce, rye, peas, green peas, carrots, tea, mustard, strawberries, celery, peppers, garlic, oats, onions, bananas, eggplant, cabbage, safflower, olives, cottage cheese, grapefruit, black walnuts, milk, soybeans, and chili peppers.

[0067] In some embodiments, the plurality of distinct food preparations are crude aqueous extracts. In other embodiments, the plurality of distinct food preparations are processed aqueous extracts. In some embodiments, the plurality of distinct food preparations are crude aqueous extracts or processed aqueous extracts.

[0068] In a particular aspect, the present invention relates to a detection device for testing food hypersensitivity to biological samples from patients diagnosed with or suspected of ADD / ADHD, comprising a solid surface with a plurality of food preparations, each food preparation being individually bound to said solid surface, at least 50% of said plurality of food preparations being ADD / ADHD trigger foods capable of reacting with immunoglobulins from said biological sample. In another embodiment, at least 55% of said plurality of food preparations being ADD / ADHD trigger foods capable of reacting with immunoglobulins from said biological sample. In another embodiment, at least 60% of said plurality of food preparations being ADD / ADHD trigger foods capable of reacting with immunoglobulins from said biological sample. In another embodiment, at least 65% of said plurality of food preparations being ADD / ADHD trigger foods capable of reacting with immunoglobulins from said biological sample. In yet another embodiment, at least 70% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In yet another embodiment, at least 75% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In another embodiment, at least 80% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In certain other embodiments, at least 85% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In other embodiments, at least 90% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In yet another embodiment, at least 95% of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample.

[0069] In some embodiments, the inducer foods are at least two food items selected from foods 1-37 of Table 2, at least three food items selected from foods 1-37 of Table 2, at least four food items selected from foods 1-37 of Table 2, at least five food items selected from foods 1-37 of Table 2, at least six food items selected from foods 1-37 of Table 2, at least seven food items selected from foods 1-37 of Table 2, at least eight food items selected from foods 1-37 of Table 2, at least two food items selected from foods 1-37 of Table 2, at least one food item ... at least 9 food items, at least 10 food items selected from foods 1 to 37 of Table 2, at least 11 food items selected from foods 1 to 37 of Table 2, at least 12 food items selected from foods 1 to 37 of Table 2, at least 13 food items selected from foods 1 to 37 of Table 2, at least 14 food items selected from foods 1 to 37 of Table 2, at least 15 food items selected from foods 1 to 37 of Table 2, at least 16 food items selected from foods 1 to 37 of Table 2, at least 1 food item selected from foods 1 to 37 of Table 2 7 food items, at least 18 food items selected from Foods 1 to 37 of Table 2, at least 19 food items selected from Foods 1 to 37 of Table 2, at least 20 food items selected from Foods 1 to 37 of Table 2, at least 21 food items selected from Foods 1 to 37 of Table 2, at least 22 food items selected from Foods 1 to 37 of Table 2, at least 23 food items selected from Foods 1 to 37 of Table 2, at least 24 food items selected from Foods 1 to 37 of Table 2, at least 25 food items selected from Foods 1 to 37 of Table 2 at least 26 food items selected from Foods 1 to 37 of Table 2; at least 27 food items selected from Foods 1 to 37 of Table 2; at least 28 food items selected from Foods 1 to 37 of Table 2; at least 29 food items selected from Foods 1 to 37 of Table 2; at least 30 food items selected from Foods 1 to 37 of Table 2; at least 31 food items selected from Foods 1 to 37 of Table 2; at least 32 food items selected from Foods 1 to 37 of Table 2; at least 33 food items selected from Foods 1 to 37 of Table 2;At least 34 food items selected from Foods 1-37 of Table 2, at least 35 food items selected from Foods 1-37 of Table 2, at least 36 food items selected from Foods 1-37 of Table 2, and at least 37 food items selected from Foods 1-37 of Table 2. In yet another embodiment, the trigger food is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soy, and chili pepper.

[0070] In some embodiments, the plurality of distinct food preparations are crude aqueous extracts. In other embodiments, the plurality of distinct food preparations are processed aqueous extracts. In some embodiments, the plurality of distinct food preparations are crude aqueous extracts or processed aqueous extracts.

[0071] In a particular aspect, the present invention relates to a detection device for testing food hypersensitivity to a biological sample from a patient diagnosed with or suspected of having ADD / ADHD, the detection device comprising a solid surface with a plurality of food preparations, each food preparation being individually bound to the solid surface, at least seven food preparations of the plurality of food preparations being ADD / ADHD trigger foods capable of reacting with immunoglobulins from the biological sample. In another embodiment, at least eight food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins from the biological sample. In another embodiment, at least nine food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins from the biological sample. In another embodiment, at least ten food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins from the biological sample. In another embodiment, at least 11 food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In another embodiment, at least 12 food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In another embodiment, at least 13 food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample. In another embodiment, at least 14 food preparations of the plurality of food preparations are ADD / ADHD trigger foods capable of reacting with immunoglobulins derived from the biological sample.

[0072] In other embodiments, the inducer foods are at least two food items selected from foods 1-37 of Table 2, at least three food items selected from foods 1-37 of Table 2, at least four food items selected from foods 1-37 of Table 2, at least five food items selected from foods 1-37 of Table 2, at least six food items selected from foods 1-37 of Table 2, at least seven food items selected from foods 1-37 of Table 2, at least eight food items selected from foods 1-37 of Table 2, at least one food item ... at least 9 food items selected from Foods 1 to 37 of Table 2, at least 10 food items selected from Foods 1 to 37 of Table 2, at least 11 food items selected from Foods 1 to 37 of Table 2, at least 12 food items selected from Foods 1 to 37 of Table 2, at least 13 food items selected from Foods 1 to 37 of Table 2, at least 14 food items selected from Foods 1 to 37 of Table 2, at least 15 food items selected from Foods 1 to 37 of Table 2, at least 16 food items selected from Foods 1 to 37 of Table 2, at least 17 food items selected from Foods 1 to 37 of Table 2 at least 18 food items selected from Foods 1 to 37 of Table 2; at least 19 food items selected from Foods 1 to 37 of Table 2; at least 20 food items selected from Foods 1 to 37 of Table 2; at least 21 food items selected from Foods 1 to 37 of Table 2; at least 22 food items selected from Foods 1 to 37 of Table 2; at least 23 food items selected from Foods 1 to 37 of Table 2; at least 24 food items selected from Foods 1 to 37 of Table 2; at least 25 food items selected from Foods 1 to 37 of Table 2 items, at least 26 food items selected from Foods 1 to 37 of Table 2, at least 27 food items selected from Foods 1 to 37 of Table 2, at least 28 food items selected from Foods 1 to 37 of Table 2, at least 29 food items selected from Foods 1 to 37 of Table 2, at least 30 food items selected from Foods 1 to 37 of Table 2, at least 31 food items selected from Foods 1 to 37 of Table 2, at least 32 food items selected from Foods 1 to 37 of Table 2, at least 33 food items selected from Foods 1 to 37 of Table 2,At least 34 food items selected from Foods 1-37 of Table 2, at least 35 food items selected from Foods 1-37 of Table 2, at least 36 food items selected from Foods 1-37 of Table 2, and at least 37 food items selected from Foods 1-37 of Table 2. In yet other embodiments, the trigger food is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soy, and chili pepper.

[0073] In some embodiments, the plurality of distinct food preparations are crude aqueous extracts. In other embodiments, the plurality of distinct food preparations are processed aqueous extracts. In some embodiments, the plurality of distinct food preparations are crude aqueous extracts or processed aqueous extracts.

[0074] In certain aspects, the present invention relates to a test kit using one or more different food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0075] In certain aspects, the present invention relates to methods using one or more different food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0076] In a particular aspect, the present invention relates to the use of one or more different food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0077] In certain aspects, the present invention relates to a detection device using one or more different food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and chili pepper.

[0078] Various objects, features, aspects and advantages of the embodiments described herein will become more apparent from the following detailed description of the embodiments, when taken in conjunction with the accompanying drawings in which like numerals represent like components.

[0079] Table 1 shows a list of food items from which the food preparation can be prepared. Table 2 shows the demographics of the foods ranked according to their two-sided FDR multiplicity adjusted p-values. Table 3 shows the demographic data of the ELISA scores according to food and gender. Table 4 shows the dietary cutoff values ​​for given percentile ranks. Table 5A shows the raw data for ADD / ADHD patients and controls along with the number of positive results based on the 90th percentile. Table 5B shows the raw data for ADD / ADHD patients and controls along with the number of positive results based on the 95th percentile. Table 6A provides statistical data summarizing the raw data for the ADD / ADHD patient population presented in Table 5A. Table 6B presents statistical data summarizing the raw data for the ADD / ADHD patient population presented in Table 5B. Table 7A shows statistical data summarizing the raw data for the control population shown in Table 5A. Table 7B presents statistical data summarizing the raw data for the control population presented in Table 5B. Table 8A shows statistical data summarizing the raw data of the ADD / ADHD patient population shown in Table 5A, transformed by logarithmic transformation. Table 8B shows statistical data summarizing the raw data of the ADD / ADHD patient population shown in Table 5B, transformed by logarithmic transformation. Table 9A shows statistical data summarizing the raw data of the control population shown in Table 5A, transformed by logarithmic transformation. Table 9B presents statistical data summarizing the raw data of the control population shown in Table 5B, transformed by logarithmic transformation. Table 10A shows statistical data for an independent T-test comparing the geometric mean number of positive foods based on the 90th percentile between the ADD / ADHD and non-ADD / ADHD samples. Table 10B shows statistical data for an independent T-test comparing the geometric mean number of positive foods based on the 95th percentile between the ADD / ADHD and non-ADD / ADHD samples. Table 11A shows statistical data for the Mann-Whitney test to compare the geometric mean number of positive foods based on the 90th percentile between the ADD / ADHD and non-ADD / ADHD samples. Table 11B shows statistical data for the Mann-Whitney test to compare the geometric mean number of positive foods based on the 95th percentile between the ADD / ADHD and non-ADD / ADHD samples. Table 12A shows the statistical data of the receiver operating characteristic (ROC) curve analysis of the data shown in Tables 5A-11A. Table 12B shows the statistical data of the receiver operating characteristic (ROC) curve analysis of the data shown in Tables 5B-11B. Table 13A shows statistical data of performance metrics in predicting ADD / ADHD status among female patients from the number of positive foods based on the 90th percentile. Table 13B shows statistical data of performance metrics in predicting ADD / ADHD status among male patients from the number of positive foods based on the 90th percentile. Table 14A shows statistical data of the performance metrics in predicting ADD / ADHD status among female patients from the number of positive foods based on the 95th percentile. Table 14B shows statistical data of performance metrics in predicting ADD / ADHD status among male patients from the number of positive foods based on the 95th percentile. [Brief description of the drawings]

[0080] [Figure 1A] FIG. 1A illustrates the ELISA signal scores of male ADD / ADHD patients and controls tested for cantaloupe. [Figure 1B] FIG. 1B illustrates the distribution of the percentage of male ADD / ADHD subjects above the 90th and 95th percentiles when tested on cantaloupe. [Figure 1C]FIG. 1C illustrates the signal distribution in females along with the 95th percentile cutoff as determined from a female control population tested for cantaloupe. [Figure 1D] FIG. 1D illustrates the distribution of the percentage of female ADD / ADHD subjects above the 90th and 95th percentiles when tested on cantaloupe. [Figure 2A] FIG. 2A illustrates the ELISA signal scores of male ADD / ADHD patients and controls tested for wheat. [Figure 2B] FIG. 2B illustrates the distribution of the percentage of male ADD / ADHD subjects above the 90th and 95th percentiles when tested on wheat. [Figure 2C] FIG. 2C illustrates the signal distribution in females along with the 95th percentile cutoff as determined from a female control population tested on wheat. [Figure 2D] FIG. 2D illustrates the distribution of the percentage of female ADD / ADHD subjects above the 90th and 95th percentiles when tested on wheat. [Figure 3A] FIG. 3A illustrates the ELISA signal scores of male ADD / ADHD patients and controls tested for tomato. [Figure 3B] FIG. 3B illustrates the distribution of the percentage of male ADD / ADHD subjects above the 90th and 95th percentiles when tested on tomatoes. [Figure 3C] FIG. 3C illustrates the signal distribution in females along with the 95th percentile cutoff as determined from a female control population tested on tomato. [Figure 3D] FIG. 3D illustrates the distribution of the percentage of female ADD / ADHD subjects above the 90th and 95th percentiles when tested on tomatoes. [Figure 4A] FIG. 4A illustrates the ELISA signal scores of male ADD / ADHD patients and controls tested for cucumber. [Figure 4B] FIG. 4B illustrates the distribution of the percentage of male ADD / ADHD subjects above the 90th and 95th percentiles when tested on cucumber. [Figure 4C] FIG. 4C illustrates the signal distribution in females along with the 95th percentile cutoff as determined from a female control population tested on cucumber. [Figure 4D] FIG. 4D illustrates the distribution of the percentage of female ADD / ADHD subjects above the 90th and 95th percentiles when tested on cucumber. [Figure 5A] FIG. 5A illustrates the distribution of ADD / ADHD subjects by the number of foods identified as trigger foods at the 90th percentile. [Figure 5B] FIG. 5B illustrates the distribution of ADD / ADHD subjects by the number of foods identified as trigger foods at the 95th percentile. [Figure 6A] FIG. 6A illustrates a box plot of the data shown in Table 5A. [Figure 6B] FIG. 6B illustrates a notched box plot of the data shown in Table 5A. [Figure 6C] FIG. 6C illustrates a box plot of the data shown in Table 5B. [Figure 6D] FIG. 6D illustrates a notched box plot of the data shown in Table 5B. [Figure 7A] FIG. 7A illustrates the ROC curve corresponding to the statistical data shown in Table 12A. [Figure 7B] FIG. 7B illustrates the ROC curve corresponding to the statistical data shown in Table 12B. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0081] The inventors have discovered that food preparations used in food tests to identify trigger foods in patients diagnosed with or suspected of ADD / ADHD are not equally well predictive and / or associated with ADD / ADHD symptoms. Indeed, various experiments have revealed that, among a wide range of different food items, certain food items are highly predictive / associated with ADD / ADHD, whereas other food items do not have any statistically significant association with ADD / ADHD.

[0082] Even more unexpectedly, the inventors have discovered that in addition to the large variability of food items, the gender-specific variability of responses in tests plays a substantial role in determining the association of food items with ADD / ADHD. As a result, based on the inventors' findings and further prospects, the test kits, detection apparatus or devices, arrays, chips or test panels and methods using same are now provided with substantially greater predictive power in selecting food items (i.e., trigger foods) that may be eliminated to reduce the signs and symptoms of ADD / ADHD.

[0083] In the following discussion, a number of exemplary embodiments of the inventive subject matter are provided. Although each embodiment represents only one combination of the inventive elements, the inventive subject matter is considered to include all possible combinations of the disclosed elements. Thus, if one embodiment includes element A, element B, and element C, and a second embodiment includes element B and element D, the inventive subject matter is also considered to include other remaining combinations of A, B, C, or D, even if not explicitly disclosed.

[0084] In some embodiments, numbers expressing quantities or ranges, when used to describe and claim certain embodiments of the present invention, should be understood to be optionally modified by the term "about". Thus, in some embodiments, the numerical parameters set forth in the written description and appended claims are approximations that may vary depending on the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and numerical parameters setting forth the broad scope of some embodiments of the present invention are approximations, the numerical values ​​set forth in the specific examples are reported as precisely as practicable. The numerical values ​​set forth in some embodiments of the present invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements. Unless the context indicates to the contrary, all ranges set forth herein should be construed as inclusive of their endpoints, and variable ranges should be construed to include only commercially practical values. Similarly, all recitations of values ​​should be construed to include intermediate values, unless the context indicates to the contrary.

[0085] As used herein and throughout the claims which follow, the meanings of "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Also, as used herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.

[0086] The term "average discrimination p-value" as used herein generally refers to the average of all p-values ​​(e.g., 0.05 or less) that indicate a particular probability as determined by raw p-values ​​or all p-values ​​(e.g., 0.1 or less) that indicate a particular probability as determined by FDR multiplicity-adjusted p-values, as determined by the analytical methods described herein (e.g., the analytical methods that produced the results summarized in Table 2 (e.g., foods 1-37 in Table 2, among others). In one embodiment, the average discrimination p-value refers to the average of all p-values ​​(e.g., 0.05 or less) that indicate a particular probability as determined by raw p-values ​​or all p-values ​​(e.g., 0.1 or less) that indicate a particular probability as determined by FDR multiplicity-adjusted p-values, as determined by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​(e.g., 0.1 or less) that are determined by raw p-values, as determined by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​(e.g., 0.09 or less) that are determined by raw p-values, as determined by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.08 as determined by the raw p-values ​​identified by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.075 as determined by the raw p-values ​​identified by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.07 as determined by the raw p-values ​​identified by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.065 as determined by the raw p-values ​​identified by the analytical methods described herein. In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.05 as determined by the raw p-values ​​identified by the analytical methods described herein.In yet another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.1 as determined by the False Discovery Rate (FDR) multiplicity-adjusted p-values ​​identified by the analytical methods described herein. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.09 as determined by the False Discovery Rate (FDR) multiplicity-adjusted p-values ​​identified by the analytical methods described herein. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.095 as determined by the False Discovery Rate (FDR) multiplicity-adjusted p-values ​​identified by the analytical methods described herein. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.09 as determined by the False Discovery Rate (FDR) multiplicity-adjusted p-values ​​identified by the analytical methods described herein. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.085 as determined by the False Discovery Rate (FDR) multiplicity-adjusted p-values ​​identified by the analytical methods described herein. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.08 as determined by the analytic methods described herein, as determined by false discovery rate (FDR) multiplicity-adjusted p-values. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.075 as determined by the analytic methods described herein, as determined by false discovery rate (FDR) multiplicity-adjusted p-values. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.07 as determined by the analytic methods described herein, as determined by false discovery rate (FDR) multiplicity-adjusted p-values. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.065 as determined by the analytic methods described herein, as determined by false discovery rate (FDR) multiplicity-adjusted p-values. In another embodiment, the average discrimination p-value refers to the average of all p-values ​​equal to or less than 0.06 as determined by the analytic methods described herein, as determined by false discovery rate (FDR) multiplicity-adjusted p-values.

[0087] The term "food preparation" as used herein refers to a solubilized aqueous extract of a particular food item (e.g., cantaloupe, wheat, milk). In certain embodiments, the particular food item is solubilized using a blender or similar device in the presence of a buffer, and the food item is processed until the structure of the food item is disrupted and the food item is rendered into a homogenous suspension or solution.

[0088] As used herein, the term "individually addressable" refers to a portion of a solid phase carrier (e.g., an ELISA well) to which a food preparation is immobilized (or bound, etc.) thereby allowing for separation of the food preparation from other food preparations immobilized to the solid phase carrier and detection of immunoglobulins (e.g., IgG or other binding molecules) capable of binding to the food preparation (or a component thereof).

[0089] As used herein, the term "a component of the food preparation" or "a component of the food preparation" refers to any part of a food preparation (e.g., protein, lipid, sugar) that has antigenicity (i.e., the ability to induce and / or provoke an immune response in a subject or patient).

[0090] The term "triggering food" as used herein refers to a food preparation or a component thereof that induces a significant increase in immune response in a subject (e.g., a patient) exposed to said food preparation or component thereof, said increase in immune response being highly correlated with the presence of disease symptoms, and may induce and / or exacerbate disease symptoms, or may result in alleviation or suppression of symptoms upon omission of said food preparation or component thereof, or both. In one embodiment, the triggering food may be characterized by a p-value determined by the raw p-value of about 0.15 or less. In another embodiment, the triggering food may be characterized by a p-value determined by the raw p-value of about 0.10 or less. In another embodiment, the triggering food may be characterized by a p-value determined by the raw p-value of about 0.075 or less. In yet another embodiment, the triggering food may be characterized by a p-value determined by the raw p-value of about 0.05 or less. In another embodiment, the attractive food may be characterized by a p-value determined by a false discovery rate (FDR) multiplicity-adjusted p-value of about 0.10 or less. In another embodiment, the attractive food may be characterized by a p-value determined by a false discovery rate (FDR) multiplicity-adjusted p-value of about 0.09 or less. In another embodiment, the attractive food may be characterized by a p-value determined by a false discovery rate (FDR) multiplicity-adjusted p-value of about 0.08 or less. In yet another embodiment, the attractive food may be characterized by a p-value determined by a false discovery rate (FDR) multiplicity-adjusted p-value of about 0.07 or less. In another embodiment, the attractive food may be characterized by one of the food preparations listed in Table 1 and / or Table 2. In another embodiment, the attractive food may be characterized by one of the food preparations listed in Table 2. In another embodiment, the inducer food may be characterized as being one of the food preparations ranked 1 to 37 in Table 2 (also referred to herein as "Foods 1 to 37 in Table 2").

[0091] All methods described herein can be performed in any suitable order unless otherwise indicated herein or clearly contradicted otherwise by context. Any and all examples provided herein with respect to certain embodiments, or the use of exemplary terminology (e.g., "such as"), are intended merely to better clarify the invention and are not intended as a limitation on the scope of the invention as otherwise claimed. No terminology in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.

[0092] The grouping of various alternative components or embodiments of the invention disclosed herein should not be construed as limiting. Each group member may be presented and claimed individually or in any combination with other members of the group or other elements found herein. One or more elements of a group may be included in or deleted from a group for convenience and / or reasons of patentability. When any inclusion or deletion is made, the specification is deemed to contain the group as amended in this case, thus fulfilling the written description of all Markush groups used in the appended claims.

[0093] Thus, in one aspect, the inventors contemplate a test kit, detection apparatus or device, array, chip or test panel that is suitable for identifying food items that induce and / or exacerbate ADD / ADHD symptoms or, if ruled out, alleviate ADD / ADHD symptoms in patients diagnosed with or suspected of ADD / ADHD. In some embodiments, such a test kit, detection device or device, array, chip or test panel will comprise one or more (e.g., a plurality) different food preparations (e.g., pre- or post-processing extracts (e.g., aqueous extracts with any co-solvent), which extracts may or may not be filtered) separately bound to individually addressable solid supports (e.g., in the form of an array or microwell plate), where the different food preparations have an average discrimination p-value of 0.07 or less as determined by a raw p-value, or an average discrimination p-value of 0.10 or less as determined by an FDR multiplicity adjusted p-value. In certain embodiments, the distinct food preparations consist essentially of food preparations each having a discriminatory p-value of 0.07 or less as determined by a raw p-value, or a discriminatory p-value of 0.10 or less as determined by an FDR multiplicity-adjusted p-value. In certain embodiments, at least 50% of the distinct food preparations each have a discriminatory p-value of 0.07 or less as determined by a raw p-value, or a discriminatory p-value of 0.10 or less as determined by an FDR multiplicity-adjusted p-value.

[0094] In some embodiments, numbers expressing properties such as amounts, concentrations, and reaction conditions of ingredients, and the like, when used to describe and claim certain embodiments of the present invention, should be understood to be modified in some cases by the term "about". Thus, in some embodiments, the numerical parameters set forth in the written description and appended claims are approximations that may vary depending on the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and numerical parameters setting forth the broad scope of some embodiments of the present invention are approximations, the numerical values ​​set forth in the specific examples are reported as precisely as practicable. The numerical values ​​set forth in some embodiments of the present invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements. Moreover, and unless the context indicates to the contrary, all ranges set forth herein should be construed as inclusive of their endpoints, and variable ranges should be construed to include only commercially practical values. Similarly, all recitations of values ​​should be construed to include intermediate values, unless the context indicates to the contrary.

[0095] Without being limiting to the subject matter of the invention, the food preparations will typically be obtained from foods commonly known or suspected to induce and / or exacerbate signs or symptoms of ADD / ADHD, or to alleviate symptoms of ADD / ADHD when excluded. Particularly suitable food preparations may be identified by the experimental procedures outlined below. Thus, it should be understood that food items (e.g., trigger foods) need not be limited to those described herein, but all items that can be identified by the methods set forth herein are contemplated. Thus, in certain embodiments, exemplary food preparations include at least two food preparations, at least four food preparations, at least eight food preparations, or at least twelve food preparations prepared from foods 1-37 in Table 2. In other embodiments, the exemplary food preparations include at least one food preparation prepared from foods 1-37 of Table 2, at least two food preparations prepared from foods 1-37 of Table 2, at least three food preparations prepared from foods 1-37 of Table 2, at least four food preparations prepared from foods 1-37 of Table 2, at least five food preparations prepared from foods 1-37 of Table 2, at least six food preparations prepared from foods 1-37 of Table 2, at least seven food preparations prepared from foods 1-37 of Table 2, at least eight food preparations prepared from foods 1-37 of Table 2, at least nine food preparations prepared from foods 1-37 of Table 2, at least one food preparation ... at least 10 food preparations prepared from foods 1 to 37 of Table 2, at least 11 food preparations prepared from foods 1 to 37 of Table 2, at least 12 food preparations prepared from foods 1 to 37 of Table 2, at least 13 food preparations prepared from foods 1 to 37 of Table 2, at least 14 food preparations prepared from foods 1 to 37 of Table 2, at least 15 food preparations prepared from foods 1 to 37 of Table 2, at least 16 food preparations prepared from foods 1 to 37 of Table 2, at least 17 food preparations prepared from foods 1 to 37 of Table 2, at least 18 food preparations prepared from foods 1 to 37 of Table 2, at least 19 food preparations prepared from foods 1 to 37 of Table 2,At least 20 food preparations prepared from foods 1 to 37 of Table 2, at least 21 food preparations prepared from foods 1 to 37 of Table 2, at least 22 food preparations prepared from foods 1 to 37 of Table 2, at least 23 food preparations prepared from foods 1 to 37 of Table 2, at least 24 food preparations prepared from foods 1 to 37 of Table 2, at least 25 food preparations prepared from foods 1 to 37 of Table 2, at least 26 food preparations prepared from foods 1 to 37 of Table 2, at least 27 food preparations prepared from foods 1 to 37 of Table 2, at least 28 food preparations prepared from foods 1 to 37 of Table 2, at least 29 food preparations prepared from foods 1 to 37 of Table 2, at least 30 food preparations prepared from foods 1 to 37 of Table 2, at least 31 food preparations prepared from foods 1 to 37 of Table 2, at least 32 food preparations prepared from foods 1 to 37 of Table 2, at least 33 food preparations prepared from foods 1 to 37 of Table 2, at least 34 food preparations prepared from foods 1 to 37 of Table 2, at least 35 food preparations prepared from foods 1 to 37 of Table 2, at least 36 food preparations prepared from foods 1 to 37 of Table 2, at least 37 food preparations prepared from foods 1 to 37 of Table 2, at least 38 food preparations prepared from foods 1 to 37 of Table 2, at least 39 food preparations prepared from foods 1 to 37 of Table 2, at least 40 food preparations prepared from foods 1 to 37 of Table 2, at least 41 food preparations prepared from foods 1 to 37 of Table 2, at least 42 food preparations prepared from foods 1 to 37 of Table 2, at least 43 at least 29 food preparations prepared from foods 1 to 37 of Table 2, at least 30 food preparations prepared from foods 1 to 37 of Table 2, at least 31 food preparations prepared from foods 1 to 37 of Table 2, at least 32 food preparations prepared from foods 1 to 37 of Table 2, at least 33 food preparations prepared from foods 1 to 37 of Table 2, at least 34 food preparations prepared from foods 1 to 37 of Table 2, at least 35 food preparations prepared from foods 1 to 37 of Table 2, at least 36 food preparations prepared from foods 1 to 37 of Table 2, and at least 37 food preparations prepared from foods 1 to 37 of Table 2. In other embodiments, the exemplary food preparation is selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soybean, and red pepper. Still further, particularly contemplated food items and food additives from which the food preparation can be prepared are listed in Table 1.

[0096] Using bodily fluids obtained from patients diagnosed with or suspected of ADD / ADHD and healthy control individuals (i.e., individuals not diagnosed with or suspected of ADD / ADHD), numerous additional food items (i.e., trigger foods) may be identified. In some embodiments, the identified food items (i.e., trigger foods) will have high discrimination power, as determined by raw p-values, having a p-value of 0.15 or less. In other embodiments, the identified food items (i.e., trigger foods) will have high discrimination power, as determined by raw p-values, having a p-value of 0.14 or less. In other embodiments, the identified food items (i.e., trigger foods) will have high discrimination power, as determined by raw p-values, having a p-value of 0.13 or less. In other embodiments, the identified food items (i.e., trigger foods) will have high discrimination power, as determined by raw p-values, having a p-value of 0.12 or less. In other embodiments, the identified food items (i.e., the attractive foods) will have high discrimination power, and as such, will have a p-value of 0.11 or less when determined by the raw p-value. In other embodiments, the identified food items (i.e., the attractive foods) will have high discrimination power, and as such, will have a p-value of 0.10 or less when determined by the raw p-value. In other embodiments, the identified food items (i.e., the attractive foods) will have high discrimination power, and as such, will have a p-value of 0.09 or less when determined by the raw p-value. In other embodiments, the identified food items (i.e., the attractive foods) will have high discrimination power, and as such, will have a p-value of 0.08 or less when determined by the raw p-value. In other embodiments, the identified food items (i.e., the attractive foods) will have high discrimination power, and as such, will have a p-value of 0.07 or less when determined by the raw p-value.In other embodiments, the identified food items (i.e., the triggering foods) will have high discrimination power, and as such, will have a p-value of 0.06 or less when determined by a raw p-value. In yet other embodiments, the identified food items (i.e., the triggering foods) will have high discrimination power, and as such, will have a p-value of 0.05 or less when determined by a raw p-value. In certain embodiments, the identified food items (i.e., the triggering foods) will have high discrimination power, and as such, will have a p-value of 0.10 or less when determined by a false discovery rate (FDR) multiplicity adjusted p-value. In other embodiments, the identified food items (i.e., the triggering foods) will have high discrimination power, and as such, will have a p-value of 0.09 or less when determined by a false discovery rate (FDR) multiplicity adjusted p-value. In other embodiments, the identified food items (i.e., the triggering foods) will have high discrimination power, and as such, will have a p-value of 0.08 or less when determined by a false discovery rate (FDR) multiplicity adjusted p-value. In yet other embodiments, the identified food items (i.e., trigger foods) will have high discriminatory power, and as such, have a p-value of 0.07 or less, as determined by a false discovery rate (FDR) multiplicity-adjusted p-value.

[0097] In certain embodiments, such identified food preparations will have high discrimination power, such as a p-value of 0.15 or less, as determined by raw p-values, a p-value of 0.10 or less, or even a p-value of 0.05 or less, and / or a p-value of 0.10 or less, a p-value of 0.08 or less, or even a p-value of 0.07 or less, as determined by false discovery rate (FDR) multiplicity adjusted p-values. In some embodiments, the identified food preparations will have high discrimination power, such as a p-value of 0.15 or less, as determined by raw p-values. In other embodiments, the identified food preparations will have high discrimination power, such as a p-value of 0.14 or less, as determined by raw p-values. In other embodiments, the identified food preparations will have high discrimination power, such as a p-value of 0.13 or less, as determined by raw p-values. In other embodiments, the identified food preparations will have high discrimination power, such as a p-value of 0.12 or less, as determined by raw p-values. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.11 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.10 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.09 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.08 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.07 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by raw p-values, having a p-value of 0.06 or less.In still other embodiments, the identified food preparations will have high discrimination power, as determined by a raw p-value, of 0.05 or less. In certain embodiments, the identified food preparations will have high discrimination power, as determined by a false discovery rate (FDR) multiplicity-adjusted p-value, of 0.10 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by a false discovery rate (FDR) multiplicity-adjusted p-value, of 0.09 or less. In other embodiments, the identified food preparations will have high discrimination power, as determined by a false discovery rate (FDR) multiplicity-adjusted p-value, of 0.08 or less. In still other embodiments, the identified food preparations will have high discrimination power, as determined by a false discovery rate (FDR) multiplicity-adjusted p-value, of 0.07 or less.

[0098] Thus, when a test kit, detection device or apparatus, array, chip or panel has a large number (i.e., a plurality) of food preparations, in certain embodiments, it is intended that the different food preparations have an average discrimination p-value of 0.05 or less as determined by raw p-values, or an average discrimination p-value of 0.08 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, the different food preparations have an average discrimination p-value of 0.025 or less as determined by raw p-values, or an average discrimination p-value of 0.07 or less as determined by FDR multiplicity-adjusted p-values. In other embodiments, it should be understood that in certain embodiments, the FDR multiplicity-adjusted p-values ​​may be adjusted for at least one of age and sex, while in still other embodiments, the FDR multiplicity-adjusted p-values ​​may be adjusted for both age and sex. On the other hand, when the test kit, detection device or apparatus, array, chip or panel is stratified for use with a single gender, it is also intended that at least 50%, or at least 55%, or at least 60%, or at least 65%, or at least 70%, or at least 75%, or at least 80%, or at least 85%, or at least 90%, or at least 95%, or all of the different food preparations in the test kit, detection device or apparatus, array, chip or panel have an average discrimination p-value of 0.07 or less when determined by raw p-value, or an average discrimination p-value of 0.10 or less when determined by FDR multiplicity adjusted p-value, when adjusted for only one gender. Furthermore, it should be understood that other stratifications (e.g., dietary preferences, ethnicity, place of residence, genetic predisposition or family history, etc.) are also contemplated, and a person skilled in the art (PHOSITA) can easily evaluate whether the stratification is appropriately selected.

[0099] The recitation of various ranges of values ​​herein is merely intended to serve as a shorthand method of individually referring to each separate value falling within that range. Unless otherwise indicated herein, each separate value is incorporated herein as if that value were individually listed herein. All methods described herein can be performed in any suitable order, unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples or exemplary terminology (e.g., "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the embodiments of the invention and is not intended as a limitation on the scope of the embodiments of the invention otherwise claimed. No terminology herein should be construed as indicating any non-claimed element essential to the practice of the invention.

[0100] It should be noted, of course, that the specific format of the test kit, detection device or apparatus, array, chip or panel may vary considerably, and contemplated formats include microwell plates, dipsticks, membrane-bound arrays, etc. As a result, the solid support to which the food preparation is bound may include the wells of a multi-well plate, (e.g., color-coded or magnetic) beads, or adsorbent films (e.g., nitrocellulose films or microporous / nanoporous polymeric films), or electrical sensors (e.g., printed copper sensors or microchips).

[0101] Thus, the inventors also contemplate a method of identifying food items that induce and / or exacerbate ADD / ADHD symptoms in a patient diagnosed with or suspected of ADD / ADHD. Most typically, such a method will include contacting a food preparation with a body fluid (e.g., including but not limited to, whole blood, plasma, serum, saliva, urine or stool suspension) of a patient diagnosed with or suspected of ADD / ADHD, where said body fluid is associated with gender specificity. As noted above, the contacting step is, in certain embodiments, performed under conditions that allow IgG (or IgE or IgA or IgM or IgD) from the body fluid to bind to at least one component of the food preparation, and then the IgG that binds to said component of the food preparation is quantified / measured to obtain a signal. In some embodiments, the signal is then compared against gender-stratified reference values ​​(e.g., at least the 90th percentile) for the food preparation using the gender identification to obtain a result, which is then used to update or create a report (e.g., a medical report, a verbal result report from the physician to the patient, a written or verbal instruction from the physician based on the result).

[0102] In certain embodiments, such methods will not be limited to just one food preparation, but will use a number of different food preparations (i.e., a plurality of different food preparations). As noted above, suitable food preparations can be identified using a variety of methods as set forth herein. In certain embodiments, the food preparations include foods 1-37 of Table 2 and / or items of Table 1. As also shown herein, in some embodiments, at least some or all of the different food preparations have an average discrimination p-value of 0.07 or less (or 0.065 or less, or 0.06 or less, or 0.055 or less, or 0.05 or less, or 0.045 or less, or 0.04 or less, or 0.035 or less, or 0.03 or less, or 0.025 or less) as determined by a raw p-value, and / or an average discrimination p-value of 0.10 or less (or 0.095 or less, or 0.09 or less, or 0.085 or less, or 0.08 or less, or 0.075 or less, or 0.07 or less) as determined by an FDR multiplicity adjusted p-value.

[0103] In certain embodiments, the food preparation is prepared from a single food item as a crude extract or crude filtered extract, although it is contemplated that the food preparation may be prepared from a mixture of multiple food items (e.g., a citrus mixture including lemon, orange, and grapefruit, a yeast mixture including baker's yeast and brewer's yeast, a rice mixture including brown rice and white rice, a sugar mixture including honey, maltose, and cane sugar, etc.) It is also contemplated that in some embodiments the food preparation may be prepared from purified or recombinant food antigens.

[0104] In certain embodiments, the food preparations provided are immobilized (typically in an addressable manner) on a solid surface, and thus the step of measuring the immunoglobulins (e.g., IgG or other types of antibodies) bound to the components of the food preparation is intended to be performed by an ELISA test. Exemplary solid surfaces include, but are not limited to, wells of a multi-well plate, since each food preparation is isolated in an individual microwell. In certain embodiments, the food preparations will be bound or immobilized on the solid surface. In other embodiments, the food preparations will be bound to a molecular label that allows binding to human immunoglobulins (e.g., IgG) in solution. See, for example, Example 3.

[0105] In a different aspect, the inventors also contemplate a method of creating a test for identifying food items that induce and / or exacerbate ADD / ADHD in diagnosed or suspected ADD / ADHD patients. Thus, in a particular embodiment, the method is for identifying trigger food items (i.e., trigger foods) in diagnosed or suspected ADD / ADHD patients. Such a test would typically include obtaining one or more test results (e.g., ELISA) for a variety of different food preparations, provided that the test results are based on bodily fluids (e.g., including but not limited to, whole blood, plasma, serum, saliva, urine, stool suspension) of diagnosed or suspected ADD / ADHD patients and bodily fluids of control groups not diagnosed or suspected ADD / ADHD. In another embodiment, the method is for identifying trigger food items (i.e., trigger foods) in patients who remain suspected of ADD / ADHD. In certain embodiments, the test results are then stratified by gender for each of the different food preparations, and different cut-off values ​​for male and female patients for each of the different food preparations (e.g., cut-off values ​​for male and female patients have a difference of at least 10% (absolute value)) are assigned for a given percentile rank (e.g., the 90th or 95th percentile).

[0106] As noted above, and without limiting the subject matter of the invention, in certain embodiments, it is contemplated that the plurality of different food preparations includes at least two (or six or ten or fifteen) food preparations prepared from food items selected from the group consisting of foods 1-37 of Table 2 and / or the items of Table 1. In other embodiments, the plurality of different food preparations includes at least one food preparation prepared from foods 1-37 of Table 2, at least two food preparations prepared from foods 1-37 of Table 2, at least three food preparations prepared from foods 1-37 of Table 2, at least four food preparations prepared from foods 1-37 of Table 2, at least five food preparations prepared from foods 1-37 of Table 2, at least six food preparations prepared from foods 1-37 of Table 2, at least one food preparation ... at least 7 food preparations prepared from foods 1 to 37 of Table 2, at least 8 food preparations prepared from foods 1 to 37 of Table 2, at least 9 food preparations prepared from foods 1 to 37 of Table 2, at least 10 food preparations prepared from foods 1 to 37 of Table 2, at least 11 food preparations prepared from foods 1 to 37 of Table 2, at least 12 food preparations prepared from foods 1 to 37 of Table 2, at least 13 food preparations prepared from foods 1 to 37 of Table 2, at least 14 food preparations prepared from foods 1 to 37 of Table 2, at least 14 food preparations prepared from foods 1 to 37 of Table 2, at least 15 food preparations prepared from foods 1 to 37 of Table 2, at least 16 food preparations prepared from foods 1 to 37 of Table 2, at least 17 food preparations prepared from foods 1 to 37 of Table 2, at least 18 food preparations prepared from foods 1 to 37 of Table 2, at least 19 food preparations prepared from foods 1 to 37 of Table 2, at least 20 food preparations prepared from foods 1 to 37 of Table 2, At least 21 food preparations prepared from foods 1-37, at least 22 food preparations prepared from foods 1-37 of Table 2, at least 23 food preparations prepared from foods 1-37 of Table 2, at least 24 food preparations prepared from foods 1-37 of Table 2, at least 25 food preparations prepared from foods 1-37 of Table 2, at least 26 food preparations prepared from foods 1-37 of Table 2, at least 27 food preparations prepared from foods 1-37 of Table 2,At least 28 food preparations prepared from foods 1-37 of Table 2, at least 29 food preparations prepared from foods 1-37 of Table 2, at least 30 food preparations prepared from foods 1-37 of Table 2, at least 31 food preparations prepared from foods 1-37 of Table 2, at least 32 food preparations prepared from foods 1-37 of Table 2, at least 33 food preparations prepared from foods 1-37 of Table 2, at least 34 food preparations prepared from foods 1-37 of Table 2, at least 35 food preparations prepared from foods 1-37 of Table 2, at least 36 food preparations prepared from foods 1-37 of Table 2, at least 37 food preparations prepared from foods 1-37 of Table 2. On the other hand, when testing new food items, it should be understood that the different food preparations include food preparations prepared from food items other than foods 1-37 of Table 2.

[0107] However, regardless of the particular selection of food items, in certain embodiments, the plurality of distinct food preparations have an average discrimination p-value of 0.07 or less (or 0.05 or less or 0.025 or less) as determined by raw p-values, or an average discrimination p-value of 0.10 or less (or 0.08 or less or 0.07 or less) as determined by FDR multiplicity adjusted p-values. In other embodiments, the plurality of distinct food preparations have an average discrimination p-value selected from the group consisting of about 0.07 or less, about 0.065 or less, about 0.06 or less, about 0.055 or less, about 0.05 or less, about 0.045 or less, about 0.04 or less, about 0.035 or less, about 0.03 or less, about 0.025 or less, and about 0.02 or less as determined by raw p-values. In yet other embodiments, the distinct food preparations have an average discrimination p-value selected from the group consisting of about 0.10 or less, about 0.095 or less, about 0.09 or less, about 0.085 or less, about 0.08 or less, about 0.075 or less, about 0.07 or less, about 0.065 or less, about 0.06 or less, about 0.055 or less, and about 0.05 or less as determined by FDR multiplicity adjusted p-values. Various exemplary aspects and protocols, as well as discussion, are provided in the experimental description below.

[0108] It should therefore be appreciated that by having a reliable testing system as described herein, the rates of false positives and false negatives can be significantly reduced (especially when the testing system and method are stratified by or adjusted for gender differences as described below). Such advantages have not been realized heretofore, and it is anticipated that the systems and methods presented herein will substantially increase the predictive power of food sensitivity testing for patients diagnosed with or suspected of having ADD / ADHD. EXAMPLES

[0109] Example 1: General protocol for making food preparations: Commercially available food extracts prepared from the edible portions of the respective raw foods (available from Biomerica Inc. 17571 Von Karman Ave, Irvine, CA 92614) were used to prepare ELISA plates according to the manufacturer's instructions.

[0110] For some food extracts, the inventors predict that food extracts prepared using certain specific procedures for making said food extracts will provide better results in detecting elevated immunoglobulin (e.g., IgG) reactivity in ADD / ADHD patients when compared to commercially available food extracts. For example, in certain embodiments relating to grains and nuts, a three-step procedure for making food extracts can be used. The first step is a defatting step. In this step, lipids from grains and nuts are extracted by contacting grain and nut flours with a non-polar solvent and collecting the residue. The defatted grain or nut flour is then extracted by contacting the flour with a high pH to obtain a mixture and removing solids from the mixture to obtain a liquid extract. Once the liquid extract is obtained, the liquid extract is stabilized by adding an aqueous formulation. In certain embodiments, the aqueous formulation includes sugar alcohols, metal chelators, protease inhibitors, inorganic salts, and buffer components (pH 4-9, 20-50 mM buffer). This formulation allowed long-term storage at -70°C and multiple freeze / thaw cycles without loss of activity.

[0111] As another example, in certain embodiments relating to meat and fish, a two-step procedure for making food extracts can be used. The first step is an extraction step, in which an extract from unprocessed, uncooked meat or fish is made by emulsifying the unprocessed, uncooked meat or fish in an aqueous buffer formulation using a high impact pressure processor. Solids are then removed to obtain a liquid extract. Once the liquid extract is obtained, the liquid extract is stabilized by adding an aqueous formulation. In certain embodiments, the aqueous formulation includes sugar alcohols, metal chelators, protease inhibitors, inorganic salts, and buffer components (20-50 mM buffer at pH 4-9). This formulation allowed for long-term storage at -70°C and multiple freeze / thaw cycles without loss of activity.

[0112] As yet another example, in certain embodiments relating to fruits and vegetables, a two-step procedure for making food extracts can be used. The first step is an extraction step. In this step, a liquid extract from fruits or vegetables is made using an extractor (e.g., a grinding juicer) to crush the food and extract the juice. The solids are then removed to obtain a liquid extract. Once the liquid extract is obtained, the liquid extract is stabilized by adding an aqueous formulation. In certain embodiments, the aqueous formulation includes sugar alcohols, metal chelators, protease inhibitors, inorganic salts, and buffer components (20-50 mM buffer with pH 4-9). This formulation allowed for long-term storage at -70°C and multiple freeze / thaw cycles without loss of activity.

[0113] Example 2: Blocking of ELISA plates: To optimize the signal-to-noise ratio, the plate is blocked with a blocking buffer, which in one embodiment contains 20-50 mM phosphate buffer at pH 4-9, bovine serum albumin (BSA), and polyvinyl alcohol (PVA).

[0114] Example 3: ELISA preparation and testing of samples: A food antigen preparation (i.e., food preparation) was immobilized on each microtiter well according to the manufacturer's instructions. For the assay, the food antigen (i.e., food preparation) was reacted with the antibodies (e.g., IgG) present in the patient's serum, and excess serum proteins were removed by a washing step. To detect IgG antibody binding, an enzyme-labeled anti-IgG antibody conjugate was reacted with the antigen-antibody complex. Color was developed by adding a substrate that reacts with the coupled enzyme. The color intensity was measured. The color intensity is directly proportional to the concentration of IgG antibodies specific for a particular food antigen.

[0115] Example 4: Methodology for determining a ranked list of foods in order of ability of ELISA signal to distinguish ADD / ADHD from control subjects:From the initial selection (e.g., 100 food items or 150 food items or more), various samples can be preanalyzed and removed due to low consumption in the intended or target population. In addition, certain food items can be used as representative of larger more inclusive food groups, especially if correlations among the various species included in the inclusive group have been established by prior testing (e.g., in both genders, although correlations for a single gender are also suitable). For example, in one embodiment, green peppers would be removed and chili peppers would be added to represent the "pepper" food group, or sweet potatoes would be removed and potatoes would be added to represent the "potato" food group. In other embodiments, the final list of foods is less than 50 food items. In another embodiment, the final list of foods is 40 food items or less.In other embodiments, the final list foods are less than 50 food items, less than 49 food items, less than 48 food items, less than 47 food items, less than 46 food items, less than 45 food items, less than 44 food items, less than 43 food items, less than 42 food items, less than 41 food items, less than 40 food items, less than 39 food items, less than 38 food items, less than 37 food items, less than 36 food items, less than 35 food items, less than 34 food items, less than 33 food items, less than 32 food items, less than 31 food items, less than 30 food items, less than 29 food items, less than 28 food items, less than 27 food items, less than 26 food items, less than 25 food items, less than 24 food items, less than 23 food items, less than 22 food items, less than 21 food items, less than 20 food items, less than 19 food items, less than 18 food items, less than 17 food items, less than 16 food items, less than 15 food items, less than 14 food items, less than 13 food items, less than 12 food items, less than 11 food items, less than 10 food items, less than 9 food items, less than 8 food items, less than 7 food items, less than 6 food items, less than 5 food items, less than 4 food items, less than 3 food items, and less than 2 food items.

[0116] A gender-neutral food list is necessary because the foods ultimately selected for the food panel will not be specific to a particular gender. Because the samples admitted will be at least initially unbalanced by gender (e.g., control: 38.6% female, ADD / ADHD: 67.1% female), differences in ELISA signal magnitude strictly due to gender are removed by modeling the signal scores for gender using a two-sample t-test and retaining the remainder for further analysis. For each of the tested foods (i.e., food preparations), the remaining signal scores are compared between ADD / ADHD and controls using permutation testing in a two-sample t-test with a relatively large number of resamplings (e.g., more than 1,000 times in certain embodiments, more than 10,000 times in other embodiments, and more than 50,000 times in still other embodiments). The Satterthwaite approximation can then be used for the denominator degrees of freedom to account for lack of homogeneity of variance, and the two-sided permutation p-values ​​will be the raw p-values ​​for each food. The False Discovery Rate (FDR) between comparisons will be adjusted by any acceptable statistical method (e.g., Benjamini-Hochberg, Family-wise Error Rate (FWER), Per Comparison Error Rate (PCER), etc.).

[0117] Foods (i.e., food preparations) were then ranked according to their two-sided FDR multiplicity-adjusted p-values. Foods with adjusted p-values ​​equal to or less than the desired FDR threshold are considered to have significantly greater signal scores in ADD / ADHD subjects than in control subjects, and are therefore considered candidates for inclusion in the food panel. Typical results representative of the outcome of this statistical method are shown in Table 2. In this case, the ranking of foods is according to the two-sided permutation T-test p-value with FDR adjustment.

[0118] Based on early experimental results, we intend that at least some food items (i.e., food preparations) will vary dramatically in their ELISA scores even for the same food preparations tested. Exemplary raw data are shown in Table 3. Therefore, as can be easily understood, data that are not stratified by gender will lose meaningful explanatory power if the same cutoff value is applied to raw data for male data and female data. To overcome such shortcomings, we intend to stratify the data by gender as follows.

[0119] Example 5: Statistical methods for cut-point selection for each food: A determination of which ELISA signal scores would constitute a "positive" response can be made by summarizing the distribution of signal scores among the control subjects. For each food (i.e., food preparation), ADD / ADHD subjects who score greater than or equal to a selected quantile of the control subject distribution are considered "positive". To attenuate the influence of any one subject on the cut-point determination, each food-specific and gender-specific data set is subjected to 1000 bootstrap resamplings. Within each bootstrap replicate, the 90th and 95th percentiles of the control signal scores are determined. Each ADD / ADHD subject in this bootstrap sample is compared to the 90th and 95% percentiles to determine whether this subject had a "positive" response. Final cut-points based on the 90th and 95th percentiles for each food and gender are calculated as the average 90th and 95th percentiles across the 1000 samples. The number of foods for which each ADD / ADHD subject rated "positive" was calculated by pooling the data across foods. Using such a method, we can then identify cutoff values ​​for a given percentile rank, which in most cases differ substantially as can be seen from Table 4.

[0120] A typical example of sex differences in blood IgG responses to cantaloupe is shown in Figures 1A-1D, where Figure 1A shows the signal distribution in men with the 95th percentile cutoff as determined from a male control population. Figure 1B shows the distribution of the percentage of male ADD / ADHD subjects above the 90th and 95th percentiles, while Figure 1C shows the signal distribution in women with the 95th percentile cutoff as determined from a female control population. Figure 1D shows the distribution of the percentage of female ADD / ADHD subjects above the 90th and 95th percentiles. In the same manner, Figures 2A-2D exemplarily show differential responses to wheat, Figures 3A-3D exemplarily show differential responses to tomato, and Figures 4A-4D exemplarily show differential responses to cucumber. 5A-5B show the distribution of ADD / ADHD subjects by the number of foods identified as trigger foods at the 90th (5A) and 95th (5B) percentiles. We contend that despite the specific food items (i.e., food preparations), the responses of males and females were significantly distinct.

[0121] It should be noted that the art does not provide any predictable food groups associated with ADD / ADHD that are stratified by gender. Therefore, the discovery of food items (i.e., food preparations) that show different responses by men and women is a surprising result, which cannot be clearly predicted in light of all currently available techniques. In other words, the selection of food items based on gender stratification has an unexpected technical effect, such as a significant improvement in the statistical significance of certain food items as trigger foods among male or female ADD / ADHD patients.

[0122] Example 6: Normalization of IgG response data: Although the raw data of the patient's IgG response results can be used to compare the strength of response between given foods, it is also contemplated that the patient's IgG response results can be normalized and indexed to obtain an infinite number for comparing the relative strength of response to a given food. For example, one or more of the patient's food-specific IgG results (e.g., IgG specific to orange and IgG specific to maltose) can be normalized to the patient's total IgG. The normalized value of the patient's IgG specific to orange can be 0.1, and the normalized value of the patient's IgG specific to maltose can be 0.3. In this situation, the relative strength of the patient's response to maltose is three times greater than that to orange. The patient's sensitivity to maltose and orange can then be indexed as such.

[0123] In another example, one or more of the patient's food-specific IgG results (e.g., shrimp-specific IgG and pork-specific IgG) can be normalized to the patient's overall average food-specific IgG results. The patient's overall average food-specific IgG can be estimated by the patient's total food-specific IgG. In this situation, the patient's specific IgG to shrimp can be normalized to the patient's average total food-specific IgG (e.g., the average IgG levels to shrimp, pork, Dungeness crab, chicken, and peas). However, it is also contemplated that the patient's overall average food-specific IgG can be estimated by the patient's IgG levels to specific types of foods from multiple tests. If the patient had previously been tested five times for sensitivity to shrimp and seven times for sensitivity to pork, the patient's new IgG value to shrimp or pork is normalized to the average of the five test results to shrimp or the average of the seven test results to pork. The normalized value of the patient's shrimp-specific IgG can be 6.0, and the normalized value of the patient's pork-specific IgG can be 1.0. In this situation, the patient now has a six-fold greater susceptibility to shrimp compared to his or her average susceptibility to shrimp, but a substantially similar susceptibility to pork. The patient's susceptibility to shrimp and pork can then be indexed based on such a comparison.

[0124] Example 7: Methodology for determining the subset of ADD / ADHD patients with food sensitivity underlying ADD / ADHD: Although food sensitivity is suspected to play a substantial role in various signs and symptoms of ADD / ADHD, some ADD / ADHD patients may not have food sensitivity underlying ADD / ADHD. Those patients will not benefit from dietary intervention to treat ADD / ADHD signs and symptoms. To determine such a subset of patients, bodily fluid samples from ADD / ADHD and non-ADD / ADHD patients can be tested by ELISA testing using the test device with up to 37 food samples.

[0125] Tables 5A and 5B provide exemplary raw data. As should be easily understood, the data shows the number of positive results from 37 sample foods based on the 90th percentile (Table 5A) or 95th percentile (Table 5B). Based on ICD-10 classification, the first column is ADD / ADHD patients (n=137) and the second column is non-ADD / ADHD patients (n=132). The mean and median number of positive foods were calculated for ADD / ADHD patients and non-ADD / ADHD patients. From the raw data shown in Tables 5A and 5B, the mean and standard deviation of the number of positive foods (i.e., trigger foods) were calculated for ADD / ADHD patients and non-ADD / ADHD patients. In addition, the number and percentage of patients who do not recognize positive foods were calculated for both ADD / ADHD and non-ADD / ADHD. Based on the 90th percentile, the number and percentage of patients with no positive food in the ADD / ADHD population is about 40% lower than the percentage of patients with no positive food in the non-ADD / ADHD population (24.1% vs. 38.6%, respectively) (Table 5A), and based on the 95th percentile, the percentage of patients with no positive food in the ADD / ADHD population is also significantly (i.e., about 40%) lower than the non-ADD / ADHD population (35.8% vs. 59.1%, respectively) (Table 5B). Therefore, it can be easily understood that ADD / ADHD patients who are not sensitive to positive foods are less likely to have food hypersensitivity underlying the signs and symptoms of ADD / ADHD.

[0126] Tables 6A and 7A show exemplary statistical data summarizing the raw data of the two patient populations shown in Table 5A. The statistical data includes normality, arithmetic mean, median, percentiles, and 95% confidence intervals (CI) for the mean and median values ​​that represent the number of positive foods (i.e., trigger foods) in ADD / ADHD and non-ADD / ADHD populations. Tables 6B and 7B show exemplary statistical data summarizing the raw data of the two patient populations shown in Table 5B. The statistical data includes normality, arithmetic mean, median, percentiles, and 95% confidence intervals (CI) for the mean and median values ​​that represent the number of positive foods in ADD / ADHD and non-ADD / ADHD populations.

[0127] Tables 8A and 9A show another exemplary statistical data summarizing the raw data of the two patient populations shown in Table 5A. In Tables 8A and 9A, the raw data was transformed by logarithmic transformation to improve data interpretation. Tables 8B and 9B show another exemplary statistical data summarizing the raw data of the two patient populations shown in Table 5B. In Tables 8B and 9B, the raw data was transformed by logarithmic transformation to improve data interpretation.

[0128] Tables 10A and 11A show exemplary statistical data for an independent T-test (Table 10A, log-transformed data) and a Mann-Whitney test (Table 11A) for comparing the geometric mean number of positive foods (i.e., trigger foods) between the ADD / ADHD and non-ADD / ADHD samples. The data shown in Tables 10A and 11A show a statistically significant difference in the geometric mean of the positive number of foods between the ADD / ADHD and non-ADD / ADHD populations. Both statistical tests show that the number of positive responses with the 37 food samples is significantly greater in the ADD / ADHD population than in the non-ADD / ADHD population, with an average discrimination p-value of 0.0001 or less. These statistical data are also illustrated as box plots in Figure 6A and notched box plots in Figure 6B.

[0129] Tables 10B and 11B show exemplary statistical data for an independent T-test (Table 10A, log-transformed data) and a Mann-Whitney test (Table 11B) for comparing the geometric mean number of positive foods (i.e., trigger foods) between the ADD / ADHD and non-ADD / ADHD samples. The data shown in Tables 10B and 11B show a statistically significant difference in the geometric mean of the positive number of foods between the ADD / ADHD and non-ADD / ADHD populations. Both statistical tests show that the number of positive responses with the 37 food samples is significantly greater in the ADD / ADHD population than in the non-ADD / ADHD population, with an average discrimination p-value of 0.0001 or less. These statistical data are also illustrated as box plots in Figure 6C and notched box plots in Figure 6D.

[0130] Table 12A shows exemplary statistical data of a receiver operating characteristic (ROC) curve analysis of the data shown in Tables 5A-11A to clarify the diagnostic power of the test used in Table 5 to distinguish ADD / ADHD subjects from non-ADD / ADHD subjects. When a cutoff criterion of more than 2 positive foods (i.e., trigger foods) is used, the test yields data with a sensitivity of 53.3% and a specificity of 76.5%, with an area under the curve (AUROC) of 0.660. The p-value for the ROC is significant at a p-value of less than 0.0001. Figure 7A illustrates the ROC curve corresponding to the statistical data shown in Table 12A. Because the statistical difference between the ADD / ADHD and non-ADD / ADHD populations is significant when the test result is censored at 2 positives, the number of foods the patient tests positive for could be used as confirmation of the primary clinical diagnosis of ADD / ADHD and whether food sensitivities may underlie the patient's ADD / ADHD signs and symptoms. Thus, the test can be used as another "acceptance" test to add to the currently available clinical criteria for diagnosing ADD / ADHD.

[0131] As shown in Tables 5A-12A and Figure 7A, based on the 90th percentile data, the number of positive foods (i.e., trigger foods) found in ADD / ADHD and non-ADD / ADHD subjects shows significant differences whether comparing the geometric mean or median of the data. The number of positive foods a person exhibits indicates the presence of ADD / ADHD in the subject. The test has a discriminatory power for detecting ADD / ADHD with a sensitivity of 53.3% and a specificity of 76.5%. In addition, the absolute number and percentage of subjects with zero positive foods are also highly different between ADD / ADHD and non-ADD / ADHD subjects, with a much smaller percentage of subjects with zero positive foods (24.1%) than non-ADD / ADHD subjects (38.6%). The data suggest that a subset of ADD / ADHD patients may have ADD / ADHD due to factors other than diet and may not benefit from dietary restrictions.

[0132] Table 12B shows exemplary statistical data of a receiver operating characteristic (ROC) curve analysis of the data shown in Tables 5B-11B to clarify the diagnostic power of the test used in Table 5 to distinguish ADD / ADHD subjects from non-ADD / ADHD subjects. When a cutoff criterion of positive foods (i.e., trigger foods) greater than 1 is used, the test yields data with a sensitivity of 47.4% and a specificity of 81.1%, with an area under the curve (AUROC) of 0.659. The p-value for the ROC is significant at a p-value of less than 0.0001. Figure 7B illustrates the ROC curve corresponding to the statistical data shown in Table 12B. Because the statistical difference between ADD / ADHD and non-ADD / ADHD populations is significant when the test result is censored at >1 positive, the number of foods a patient tests positive for could be used as confirmation of the primary clinical diagnosis of ADD / ADHD and whether food sensitivities may underlie the patient's ADD / ADHD signs and symptoms. Thus, the test can be used as another "acceptance" test to add to the currently available clinical criteria for diagnosing ADD / ADHD.

[0133] As shown in Tables 5B-12B and Figure 7B, based on the 95th percentile data, the number of positive foods (i.e., trigger foods) found in ADD / ADHD and non-ADD / ADHD subjects shows significant differences whether comparing the geometric mean or median of the data. The number of positive foods a person exhibits indicates the presence of ADD / ADHD in the subject. The test has a discriminatory power for detecting ADD / ADHD with a sensitivity of 47.4% and a specificity of 81.1%. In addition, the absolute number and percentage of subjects with zero positive foods are also highly different between ADD / ADHD and non-ADD / ADHD subjects, with a much smaller percentage of subjects with zero positive foods (35.8%) than non-ADD / ADHD subjects (59.1%). The data suggest that a subset of ADD / ADHD patients may have ADD / ADHD due to factors other than diet and may not benefit from dietary restrictions.

[0134] Example 8: Method for determining the distribution of the number of foods per capita declared "positive": To determine the distribution of the number of "positive" foods (i.e., trigger foods) per person and to estimate the diagnostic performance, an analysis is performed on the 37 food items from Table 2, which show the most positive response for ADD / ADHD patients. To attenuate the influence of any one subject on the analysis, each food-specific and gender-specific data set is subjected to 1000 bootstrap resamplings. Gender-specific cut-points are then determined for each food item in the bootstrap samples using the 90th and 95th percentiles of the control population. Once the gender-specific cut-points are determined, they are compared to the observed ELISA signal scores for both control and ADD / ADHD subjects. In this comparison, if the observed signal is equal to or greater than the cut-point value, the signal is determined to be a "positive" food, and if the observed signal is less than the cut-point value, the signal is determined to be a "negative" food.

[0135] Once all food items (i.e., food preparations) have been determined to be either positive or negative, the results of the 74 (37 foods × 2 cutpoint calls) for each subject are saved within each bootstrap replicate. Then, for each subject, the 37 calls are summed to obtain the “# of Positive Foods (90th)” using the 90th percentile as the cutpoint, and the remaining 37 calls are summed to obtain the “# of Positive Foods (95th)” using the 95th percentile. Then, within each replicate, the “# of Positive Foods (90th)” and “# of Positive Foods (95th)” are summarized across subjects to obtain descriptive statistics for each replicate as follows: 1) overall mean equal to the mean of the means; 2) overall standard deviation equal to the mean of the standard deviations; 3) overall median equal to the mean of the medians; 4) overall minimum equal to the minimum of the minimums; and 5) overall maximum equal to the maximum of the maximums. In this analysis, to avoid non-integer "number of positive foods" when calculating frequency distributions and histograms, the authors ensure that 1000 repetitions of the same original data set were in fact 999 sets of new subjects of the same size added to the original sample. Once the data was compiled, frequency distributions and histograms were obtained for both "number of positive foods (ranked 90)" and "number of positive foods (ranked 95)" for both genders and for both ADD / ADHD and control subjects using the programs "a_pos_foods.sas,a_pos_foods_by_dx.sas".

[0136] Example 9: Methods for estimating diagnostic performance: To estimate the diagnostic performance for each food item (i.e., food preparation) for each subject, we use the data for “Number of Positive Foods (ranked 90)” and “Number of Positive Foods (ranked 95)” for each subject in each bootstrap replicate above. In this analysis, the cut point was set to 1. Thus, if a subject has one or more "Number of Positive Foods (90th)", the subject is called "has ADD / ADHD". If a subject has less than one "Number of Positive Foods (90th)", the subject is called "Does not have ADD / ADHD". When all calls were made, these calls were compared to the actual diagnoses to determine whether the call was a true positive (TP), true negative (TN), false positive (FP) or false negative (FN). The comparisons were pooled across subjects to obtain performance metrics of sensitivity, specificity, positive predictive value and negative predictive value for both "Number of Positive Foods (90th)" and "Number of Positive Foods (95th)" when the cut point is set to 1 for each method. Each (sensitivity, 1-specificity) pair becomes a point on the ROC curve for this replicate.

[0137] To increase precision, the above analysis is repeated by gradually increasing the cut point from 2 to 37 and for each of the 1000 bootstrap replicates. The performance metrics across the 1000 bootstrap replicates are then summarized by calculating the mean using the program “t_pos_foods_by_dx.sas”. The diagnostic performance results for females and males are shown in Tables 13A and 13B (90th percentile) and Tables 14A and 14B (95th percentile).

[0138] Of course, it must be understood that certain variations in the food preparations can be made without changing the inventive subject matter presented herein. For example, when the food item was yellow onion, it must be understood that the item also includes other onion varieties that have been demonstrated to have equivalent activity in testing. In fact, the inventors note that for each tested food preparation, certain other related food preparations have also been tested in the same or equivalent manner (data not shown). Thus, it must be understood that each tested and claimed food preparation will have equivalent related preparations with demonstrated equivalent or equivalent response in testing.

[0139] In addition to the modifications already described, it will be apparent to one skilled in the art that many more modifications are possible without departing from the inventive concept herein. Thus, the subject matter of the present invention is not limited except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprising" should be interpreted as indicating elements, components, or steps in a non-exclusive manner, indicating that the indicated elements, components, or steps may be present together with, or may be utilized with, or may be combined with, other elements, components, or steps not expressly indicated. When the specification, claims indicate at least one of something selected from the group consisting of A, B, C, ..., and N, this language should be interpreted as requiring only one from this group, not A+N, or B+N, etc.

[0140] [Table 1]

[0141]

Table 2-1

[0142]

Table 2-2

[0143]

Table 2-3

[0144]

Table 3-1

[0145]

Table 3-2

[0146]

Table 3-3

[0147]

Table 3-4

[0148]

Table 3-5

[0149]

Table 3-6

[0150]

Table 3-7

[0151]

Table 3-8

[0152]

Table 3-9

[0153]

Table 3-10

[0154]

Table 3-11

[0155]

Table 3-12

[0156]

Table 3-13

[0157]

Table 3-14

[0158]

Table 3-15

[0159]

Table 3-16

[0160]

Table 4-1

[0161]

Table 4-2

[0162]

Table 4-3

[0163]

Table 5A-1

[0164]

Table 5A-2

[0165]

Table 5A-3

[0166]

Table 5A-4

[0167]

Table 5B-1

[0168]

Table 5B-2

[0169]

Table 5B-3

[0170]

Table 5B-4

[0171]

Table 6A

[0172]

Table 6B

[0173]

Table 7A

[0174]

Table 7B

[0175]

Table 8A

[0176]

Table 8B

[0177]

Table 9A

[0178]

Table 9B

[0179] [Table 10A]

[0180]

Table 10B

[0181]

Table 11A

[0182]

Table 11B

[0183]

Table 12A

[0184]

Table 12B

[0185]

Table 13A-1

[0186]

Table 13A-2

[0187]

Table 13B-1

[0188]

Table 13B-2

[0189]

Table 14A-1

[0190]

Table 14A-2

[0191]

Table 14B-1

[0192]

Table 14B-2

Claims

1. 1. A test kit panel for testing IgG reactivity, the test being for patients diagnosed with or suspected of having Attention Deficit Disorder / Attention Deficit Hyperactivity Disorder (ADD / ADHD), comprising: a plurality of different food preparations immobilized on individually addressable solid supports; wherein all of the plurality of different food preparations bound to the solid support are selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, soy, chili pepper, tobacco, malt, cinnamon, cane sugar, and potato; A test kit panel, wherein at least 10 different food preparations are bound to said solid support.

2. 2. The test kit panel of claim 1, wherein the plurality of different food preparations comprises food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, grapefruit, black walnut, milk, and soybean.

3. 10. The test kit panel of claim 1, wherein the plurality of different food preparations comprises food preparations selected from the group consisting of cantaloupe, wheat, tomato, cucumber, squash, almond, egg, cauliflower, pinto, broccoli, orange, butter, corn, lettuce, rye, peach, green pea, carrot, tea, mustard, strawberry, celery, bell pepper, garlic, oats, onion, banana, eggplant, cabbage, safflower, olive, cottage cheese, and grapefruit.

4. 10. The test kit panel of claim 1, wherein at least 20 different food preparations are bound to said solid support.

5. 10. The test kit panel of claim 1, wherein at least 30 different food preparations are bound to said solid support.

6. 10. The test kit panel of claim 1, wherein the plurality of different food preparations comprises a crude filtered aqueous extract or a processed aqueous extract.

7. 10. The test kit panel of claim 1, wherein the solid support is selected from the group consisting of a multi-well plate, an array, a dipstick, a membrane-bound array, a bead, an electrical sensor, a chemical sensor, a microchip, and an absorbent film.

8. 1. A method for testing for food hypersensitivity, comprising administering to a patient diagnosed with or suspected of having ADD / ADHD, the method comprising:

8. A method of treating a patient with ADD / ADHD, comprising contacting a plurality of different food preparations of a test kit panel according to any one of claims 1 to 7 with a body fluid of a patient diagnosed with or suspected of having ADD / ADHD, the method comprising: wherein the body fluid contains immunoglobulin, said contacting step being carried out under conditions that allow IgG from said bodily fluid to bind to at least one component of each of said different food preparations; measuring IgG bound to at least one component of each of said plurality of different food preparations to obtain a signal; comparing said signal with a predefined percentile cutoff value, wherein said predefined percentile cutoff value for each different food preparation is set as the signal at the 90th percentile of a control group; and identifying one or more of the different food preparations that are positive for patients known to have or suspected of having ADD / ADHD based on the comparison of the signal with the predetermined percentile rank cutoff value.

9. 9. The method of claim 8, wherein the patient's bodily fluid is selected from the group consisting of whole blood, plasma, serum, saliva, urine and a fecal suspension.

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