The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model

The Etiology of IgE-Mediated Food Allergy: Potential Therapeutics and Challenges

Immunoglobulin E (IgE)-mediated food allergy has been dramatically increasing in incidence over the last few decades. The combinations of both genetic and environmental factors that affect the microbiome and immune system have demonstrated significant roles in its pathogenesis. The morbidity, and at times mortality, that occurs as the result of this specific, reproducible, but impaired immune response is due to the nature of the shift from a regulatory T (Treg) cellular response to a T helper 2 (Th2) cellular response. This imbalance caused by food allergens results in an interleukin (IL)-4 and IL-13 dominant environment that drives B cell activation and differentiation into IgE-producing plasma cells. The resulting symptoms can range from mild to more severe anaphylaxis, and even death. Current therapeutic strategies involve avoidance and broad symptom management upon accidental exposure; however, no definitive cure exists. This narrative review highlights how the elucidation of the pathogenesis of IgE-mediated food allergy resulted in the development of therapeutics that are more specific to these individual receptors and molecules which have been relatively successful in mitigating this potentially life-threatening allergic response. However, potential adverse effects and re-sensitization following the conclusion of treatment has urged the need for improved therapeutic methods. Therefore, given the understanding of their mechanism of action and the overlap with the mechanism of IgE-mediated food allergies, probiotics and small molecule natural compounds may provide novel therapeutic and preventative strategies. This is compelling, as they have demonstrated success in clinical trials and may provide hope to improve quality of life in allergy patients.

Safety and adherence of early oral immunotherapy for peanut allergy in a primary care setting: a retrospective cross-sectional study

BACKGROUND

Peanut allergy is a common food allergy with potentially life-threatening implications. Early oral immunotherapy for peanut allergy (P-EOIT) has been shown to be effective and safe in research and specialty clinic settings. Provision of P-EOIT in primary care would make it available to more patients. We sought to assess the safety of P-EOIT in a primary care setting by documenting the rates of peanut-related allergic reactions leading to emergency department (ED) visits and use of epinephrine. We also examined adherence by assessing the percentage of patients reaching maintenance phase and continuing ingestion after one year of P-EOIT.

METHODS

This retrospective study included all patients aged less than 36 months who started P-EOIT at a primary care allergy clinic in New Brunswick, Canada, from 2016 to 2020. The population included patients who (1) had a history of an allergic reaction to peanuts with a positive skin prick test or positive peanut specific IgE level (ps-IgE) or (2) no history of ingestion and a baseline ps-IgE ≥5 kU/L. Patients had biweekly clinic visits with graded increases in peanut protein up to a maintenance dose of 300 mg of peanut protein daily. A blinded retrospective review of paper charts and electronic medical records was conducted along with phone interviews regarding ED visits and epinephrine use.

RESULTS

All 69 consented patients reached maintenance dose over a median of 29 weeks, and 66 patients (95.7%) were still regularly consuming peanut protein after 1 year of maintenance. One patient had a peanut ingestion-related ED visit requiring epinephrine during the escalation phase of peanut protein dosing (1.4%). During the first year of maintenance phase, no patients had peanut ingestion-related ED visits nor required epinephrine.

CONCLUSION

Early oral immunotherapy for peanut allergy in a primary care setting appears to be safe and our findings suggest that it does not lead to an increased burden of emergency department visits. Our population had high adherence rates, with the majority achieving maintenance dose and staying on this dose for one year.

Risk subgroups and intervention effects among infants at high risk for peanut allergy: A model for clinical decision making

BACKGROUND

The Learning Early About Peanut Allergy (LEAP) trial showed that early dietary introduction of peanut reduced the risk of developing peanut allergy by age 60 months in infants at high risk for peanut allergy. In this secondary analysis of LEAP data, we aimed to determine risk subgroups within these infants and estimate their respective intervention effects of early peanut introduction.

METHODS

LEAP raw data were retrieved from ITNTrialShare.org. Conditional random forest was applied to participants in the peanut avoidance arm to select statistically important features for the classification and regression tree (CART) analysis to group infants based on their risk of peanut allergy at 60 months of age. Intervention effects were estimated for each derived risk subgroup using data from both arms. Our main model was generated based on baseline data when the participants were 4-11 months old. Specific IgE measurements were truncated to account for the limit of detection commonly used by laboratories in clinical practice.

RESULTS

The model found infants with higher predicted probability of peanut allergy at 60 months of age had a similar relative risk reduction, but a greater absolute risk reduction in peanut allergy with early introduction of peanut, than those with lower probability. The intervention effects were significant across all risk subgroups. Participants with baseline peanut sIgE ≥0.22 kU/L (n = 78) had an absolute risk reduction of 40.4% (95% CI 27.3, 51.9) whereas participants with baseline peanut sIgE<0.22 kU/L and baseline Ara h 2 sIgE <0.10 kU/L (n = 226) had an absolute risk reduction of 6.5% (95% CI 2.6, 11.0). These findings were consistent in sensitivity analyses using alternative models.

CONCLUSION

In this study, risk subgroups were determined among infants from the LEAP trial based on the probability of developing peanut allergy and the intervention effects of early peanut introduction were estimated. This may be relevant for further risk assessment and personalized clinical decision-making.

Systematic review and meta-analyses on the accuracy of diagnostic tests for IgE-mediated food allergy

The European Academy of Allergy and Clinical Immunology (EAACI) is updating the Guidelines on Food Allergy Diagnosis. We aimed to undertake a systematic review of the literature with meta-analyses to assess the accuracy of diagnostic tests for IgE-mediated food allergy. We searched three databases (Cochrane CENTRAL (Trials), MEDLINE (OVID) and Embase (OVID)) for diagnostic test accuracy studies published between 1 October 2012 and 30 June 2021 according to a previously published protocol (CRD42021259186). We independently screened abstracts, extracted data from full texts and assessed risk of bias with QUADRAS 2 tool in duplicate. Meta-analyses were undertaken for food-test combinations for which three or more studies were available. A total of 149 studies comprising 24,489 patients met the inclusion criteria and they were generally heterogeneous. 60.4% of studies were in children ≤12 years of age, 54.3% were undertaken in Europe, ≥95% were conducted in a specialized paediatric or allergy clinical setting and all included oral food challenge in at least a percentage of enrolled patients, in 21.5% double-blind placebo-controlled food challenges. Skin prick test (SPT) with fresh cow's milk and raw egg had high sensitivity (90% and 94%) for milk and cooked egg allergies. Specific IgE (sIgE) to individual components had high specificity: Ara h 2-sIgE had 92%, Cor a 14-sIgE 95%, Ana o 3-sIgE 94%, casein-sIgE 93%, ovomucoid-sIgE 92/91% for the diagnosis of peanut, hazelnut, cashew, cow's milk and raw/cooked egg allergies, respectively. The basophil activation test (BAT) was highly specific for the diagnosis of peanut (90%) and sesame (93%) allergies. In conclusion, SPT and specific IgE to extracts had high sensitivity whereas specific IgE to components and BAT had high specificity to support the diagnosis of individual food allergies.

Epitope-Based IgE Assays and Their Role in Providing Diagnosis and Prognosis of Food Allergy

With advances in molecular and computational science, epitope-specific IgE antibody profiling has been developed and recently brought into clinical practice. Epitope-based testing detects IgE antibodies that directly bind to antigenic sites of an allergen, providing increased resolution specificity and fewer false-positive results for diagnosing food allergy. Epitope-binding profiles may also serve as prognostic markers of food allergy and help predict quantities of allergen that would provoke a reaction (ie, eliciting dose, possible severity of a reaction after allergen ingestion, and outcomes of treatment options such as oral immunotherapy [OIT]). Future studies are under way to discover additional applications of epitope-specific antibodies for multiple food allergens.

IgE cross-inhibition between Ara h 1 and Ara h 2 is explained by complex formation of both major peanut allergens

BACKGROUND

Surprisingly, IgE cross-reactivity between the major peanut allergens Ara h 1, 2, and 3 has been reported despite very low sequence identities.

OBJECTIVE

We investigated the unexpected cross-reactivity between peanut major allergens.

METHODS

Cross-contamination of purified natural Ara h 1, 2, 3, and 6 was assessed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), Western blot test, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and sandwich enzyme-linked immunosorbent assay (ELISA). IgE cross-reactivity was studied with sera of peanut-allergic patients (n = 43) by ELISA and ImmunoCAP inhibition using both intact natural and recombinant allergens and synthetic peptides representing postulated Ara h 1 and Ara h 2 cross-reactive epitopes.

RESULTS

Both purified nAra h 1 and nAra h 3 were demonstrated to contain small but significant amounts of Ara h 2 and Ara h 6 (<1%) by sandwich ELISA, SDS-PAGE/Western blot analysis, and LC-MS/MS. IgE cross-inhibition between both 2S albumins and Ara h 1 and Ara h 3 was only observed when using natural purified allergens, not recombinant allergens or synthetic peptides. Apparent cross-reactivity was lost when purified nAra h 1 was pretreated under reducing conditions, suggesting that Ara h 2 and Ara h 6 contaminations may be covalently bound to Ara h 1 via disulfide interactions.

CONCLUSION

True cross-reactivity of both peanut 2S albumins with Ara h 1 and Ara h 3 could not be demonstrated. Instead, cross-contamination with small quantities was shown to be sufficient to cause significant cross-inhibition that can be misinterpreted as molecular cross-reactivity. Diagnostic tests using purified nAra h 1 and nAra h 3 can overestimate their importance as major allergens as a result of the presence of contaminating 2S albumins, making recombinant Ara h 1 and Ara h 3 a preferred alternative.

Developing a Prediction Model for Determination of Peanut Allergy Status in the Learning Early About Peanut Allergy (LEAP) Studies

BACKGROUND

The Learning Early About Peanut Allergy (LEAP) study team developed a protocol-specific algorithm using dietary history, peanut-specific IgE, and skin prick test (SPT) to determine peanut allergy status if the oral food challenge (OFC) could not be administered or did not provide a determinant result.

OBJECTIVE

To investigate how well the algorithm determined allergy status in LEAP; to develop a new prediction model to determine peanut allergy status when OFC results are not available in LEAP Trio, a follow-up study of LEAP participants and their families; and to compare the new prediction model with the algorithm.

METHODS

The algorithm was developed for the LEAP protocol before the analysis of the primary outcome. Subsequently, a prediction model was developed using logistic regression.

RESULTS

Using the protocol-specified algorithm, 73% (453/617) of allergy determinations matched the OFC, 0.6% (4/617) were mismatched, and 26% (160/617) participants were nonevaluable. The prediction model included SPT, peanut-specific IgE, Ara h 1, Ara h 2, and Ara h 3. The model inaccurately predicted 1 of 266 participants as allergic who were not allergic by OFC and 8 of 57 participants as not allergic who were allergic by OFC. The overall error rate was 9 of 323 (2.8%) with an area under the curve of 0.99. The prediction model additionally performed well in an external validation cohort.

CONCLUSION

The prediction model performed with high sensitivity and accuracy, eliminated the problem of nonevaluable outcomes, and can be used to estimate peanut allergy status in the LEAP Trio study when OFC is not available.

EAACI Molecular Allergology User's Guide 2.0

Since the discovery of immunoglobulin E (IgE) as a mediator of allergic diseases in 1967, our knowledge about the immunological mechanisms of IgE-mediated allergies has remarkably increased. In addition to understanding the immune response and clinical symptoms, allergy diagnosis and management depend strongly on the precise identification of the elicitors of the IgE-mediated allergic reaction. In the past four decades, innovations in bioscience and technology have facilitated the identification and production of well-defined, highly pure molecules for component-resolved diagnosis (CRD), allowing a personalized diagnosis and management of the allergic disease for individual patients. The first edition of the "EAACI Molecular Allergology User's Guide" (MAUG) in 2016 rapidly became a key reference for clinicians, scientists, and interested readers with a background in allergology, immunology, biology, and medicine. Nevertheless, the field of molecular allergology is moving fast, and after 6 years, a new EAACI Taskforce was established to provide an updated document. The Molecular Allergology User's Guide 2.0 summarizes state-of-the-art information on allergen molecules, their clinical relevance, and their application in diagnostic algorithms for clinical practice. It is designed for both, clinicians and scientists, guiding health care professionals through the overwhelming list of different allergen molecules available for testing. Further, it provides diagnostic algorithms on the clinical relevance of allergenic molecules and gives an overview of their biology, the basic mechanisms of test formats, and the application of tests to measure allergen exposure.

Changes in Serum Protein-Peptide Patterns in Atopic Children Allergic to Plant Storage Proteins

Next to cow's milk and eggs, plant foods, i.e., legumes, tree nuts and cereal grains, most often sensitise atopic children. Storage proteins constitutes the most relevant protein fraction of plant foods, causing primary sensitisation. They exhibit strong allergenic properties and immunogenicity. Our goal was to analyse sensitisation to 26 plant storage proteins in a group of 76 children aged 0-5 years with chronic symptoms of atopic dermatitis using Allergy Explorer ALEX2 and to discover changes in serum protein-peptide patterns in allergic patients with the use of MALDI-TOF-MS. We reported that 25% of children were allergic to 2S albumins, 19.7% to 7S globulins, 13.2% to 11S globulins and 1.3% to cereal prolamins. The most common allergenic molecules were Ara h 1 (18.4%), Ara h 2 (17.1%), Ara h 6 (15.8%) and Ara h 3 (11.8%) from peanuts, and the mean serum sIgE concentrations in allergic patients were 10.93 kUA/L, 15.353 kUA/L, 15.359 kUA/L and 9.038 kUA/L, respectively. In children allergic to storage proteins compared to the other patients (both allergic and non-allergic), the cell cycle control protein 50A, testis-expressed sequence 13B, DENN domain-containing protein 5A and SKI family transcriptional corepressor 2 were altered. Our results indicate that the IgE-mediated allergy to storage proteins is a huge problem in a group of young, atopic children, and show the potential of proteomic analysis in the prediction of primary sensitisation to plant foods. It is the next crucial step for understanding the molecular consequences of allergy to storage proteins.

Are peanut oral food challenges still useful? An evaluation of children with suspected peanut allergy, sensitization to Ara h 2 and controlled asthma

BACKGROUND

Sensitization to Ara h 2 has been proposed as a promising biological marker for the severity of peanut allergy and may reduce the need for oral food challenges. This study aimed to evaluate whether peanut oral food challenge is still a useful diagnostic tool for children with suspected peanut allergy and an elevated level of Ara h 2-specific IgE. Additionally, we assessed whether well-controlled asthma is an additional risk for severe reactions.

METHODS

A retrospective analysis of 107 children with sensitization to Ara h 2-specific IgE (> 0.35 kU/l) undergoing open peanut challenges during 2012-2018 in the Tampere University Hospital Allergy Centre, Finland.

RESULTS

Of the 107 challenges, 82 (77%) were positive. Serum levels of Ara h 2 -sIgE were higher in subjects with a positive challenge than in those who remained negative (median 32.9 (IQR 6.7-99.8) vs. 2.1 (IQR 1.0-4.9) kU/l), p < 0.001) but were not significantly different between subjects with and without anaphylaxis. No correlation was observed between the serum level of Ara h 2-sIgE and reaction severity grading. Well-controlled asthma did not affect the challenge outcome.

CONCLUSIONS

Elevated levels of Ara h 2-specific IgE are associated with a positive outcome in peanut challenges but not a reliable predictor of reaction severity. Additionally, well-controlled asthma is not a risk factor for severe reactions in peanut challenges in children with sensitization to Ara h 2.

Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model

BACKGROUND

Peanut allergy (PA) has become a clinical and public health problem, which is mainly regulated by genetics, immune responses, and environmental factors. Diagnosis and treatment for PA have always remained huge challenges due to its multiple triggers. Studies have shown that long non-coding RNAs (lncRNAs) play a critical role in the development of allergic diseases.

METHOD AND RESULTS

In the current study, we examined the plasma lncRNA expression profiles of peanut allergy Brown Norway rats and healthy controls and 496 differently expressed lncRNAs were identified, including 411 up-regulated genes and 85 down-regulated genes. We screened 8 lncRNAs based on the candidate principle and the candidates were verified in individual samples by quantitative real-time PCR. Then, the four lncRNA-based diagnostic model was established by least absolute shrinkage and selection operator (LASSO) and logistic regression, which was proved by area under the receiver operating characteristic curve (AUC).

CONCLUSIONS

In summary, we assessed the correlation between lncRNA expression levels and the diagnosis of peanut allergy, which may perform a vital role in guiding the management of peanut allergy.

The Indirect Basophil Activation Test Is a Safe, Reliable, and Accessible Tool to Diagnose a Peanut Allergy in Children

BACKGROUND

The gold standard for the diagnosis of a peanut allergy is an oral food challenge (OFC), but it is a time-consuming, patient-unfriendly, and expensive test. The in vitro direct basophil activation test (BAT) for peanuts was shown to be a promising diagnostic tool for replacing the OFC.

OBJECTIVE

To determine the diagnostic accuracy of the indirect (passive) BAT. Compared with the direct BAT, the timing of the indirect BAT is more flexible, and the problem of nonresponding basophils (unresponsive to IgE receptor-mediated signaling) is circumvented.

METHODS

In 74 children, suspected of peanut allergy and eligible for an OFC, indirect BAT results for peanut extract, Ara h2, and Ara h6 were compared with the results of a double-blind placebo-controlled food challenge. The reactivity and sensitivity of the basophils in the BAT were correlated to both the allergy status and the threshold dose in the OFC.

RESULTS

The combined basophil reactivity for Ara h2 and Ara h6 showed the highest accuracy (94%) for the diagnosis of a peanut allergy, with positive and negative predictive values of 96% and 89%, respectively. The sensitivity of the basophils for Ara h2 significantly discriminates between patients who tolerated up to 0.4 g of peanut protein in the OFC and those who did not.

CONCLUSIONS

Because the indirect BAT showed a high diagnostic accuracy for peanut allergy, it is a promising alternative to the classical direct BAT and could lead to a reduction in OFC use.

Estimating the Risk of Severe Peanut Allergy Using Clinical Background and IgE Sensitization Profiles

Background: It is not well-understood why symptom severity varies between patients with peanut allergy (PA). Objective: To gain insight into the clinical profile of subjects with mild-to-moderate and severe PA, and investigate individual and collective predictive accuracy of clinical background and IgE to peanut extract and components for PA severity. Methods: Data on demographics, patient history and sensitization at extract and component level of 393 patients with probable PA (symptoms ≤ 2 h + IgE sensitization) from 12 EuroPrevall centers were analyzed. Univariable and penalized multivariable regression analyses were used to evaluate risk factors and biomarkers for severity. Results: Female sex, age at onset of PA, symptoms elicited by skin contact with peanut, family atopy, atopic dermatitis, house dust mite and latex allergy were independently associated with severe PA; birch pollen allergy with mild-to-moderate PA. The cross-validated AUC of all clinical background determinants combined (0.74) was significantly larger than the AUC of tests for sensitization to extract (0.63) or peanut components (0.54-0.64). Although larger skin prick test wheal size, and higher IgE to peanut extract, Ara h 1 and Ara h 2/6, were associated with severe PA, and higher IgE to Ara h 8 with mild-to-moderate PA, addition of these measurements of sensitization to the clinical background model did not significantly improve the AUC. Conclusions: Models combining clinical characteristics and IgE sensitization patterns can help establish the risk of severe reactions for peanut allergic patients, but clinical background determinants are most valuable for predicting severity of probable PA in an individual patient.

From Allergen Molecules to Molecular Immunotherapy of Nut Allergy: A Hard Nut to Crack

Peanuts and tree nuts are two of the most common elicitors of immunoglobulin E (IgE)-mediated food allergy. Nut allergy is frequently associated with systemic reactions and can lead to potentially life-threatening respiratory and circulatory symptoms. Furthermore, nut allergy usually persists throughout life. Whether sensitized patients exhibit severe and life-threatening reactions (e.g., anaphylaxis), mild and/or local reactions (e.g., pollen-food allergy syndrome) or no relevant symptoms depends much on IgE recognition of digestion-resistant class I food allergens, IgE cross-reactivity of class II food allergens with respiratory allergens and clinically not relevant plant-derived carbohydrate epitopes, respectively. Accordingly, molecular allergy diagnosis based on the measurement of allergen-specific IgE levels to allergen molecules provides important information in addition to provocation testing in the diagnosis of food allergy. Molecular allergy diagnosis helps identifying the genuinely sensitizing nuts, it determines IgE sensitization to class I and II food allergen molecules and hence provides a basis for personalized forms of treatment such as precise prescription of diet and allergen-specific immunotherapy (AIT). Currently available forms of nut-specific AIT are based only on allergen extracts, have been mainly developed for peanut but not for other nuts and, unlike AIT for respiratory allergies which utilize often subcutaneous administration, are given preferentially by the oral route. Here we review prevalence of allergy to peanut and tree nuts in different populations of the world, summarize knowledge regarding the involved nut allergen molecules and current AIT approaches for nut allergy. We argue that nut-specific AIT may benefit from molecular subcutaneous AIT (SCIT) approaches but identify also possible hurdles for such an approach and explain why molecular SCIT may be a hard nut to crack.

Peanut components measured by ISAC: comparison with ImmunoCap and clinical relevance in peanut allergic children

Background

Specific IgE (sIgE) against the peanut component Arachis hypogaea (Ara h) 2 has been shown to be the most important allergen to discriminate between peanut allergy and peanut tolerance. Several studies determined sIgE cut off values for Ara h 2, determined by singleplex measurements. However, cut off values for Ara h 2 from multiplex arrays are less well defined. The aim of this study was to evaluate the correlation between Ara h 2 sIgE determined by singleplex versus multiplex measurements and to assess the diagnostic value of the different peanut components included in Immuno Solid-phase Allergen Chip (ISAC) multiplex analysis in children with a suspected peanut allergy.

Methods

In this retrospective study we analyzed Ara h 2 sIgE values with singleplex Fluorescence Enzyme Immunoassay (FEIA, ImmunoCap) and multiplex microarray (ISAC) measurements in 117 children with a suspected peanut allergy. Also, other peanut components measured by ISAC were analyzed. Double blinded placebo controlled oral food challenges were used as golden standard.

Results

Among all studied peanut components FEIA Ara h 2 sIgE showed the highest area under the curve (AUC, 0.922), followed by ISAC Ara h 6 and Ara h 2 sIgE with AUCs of respectively 0.906 and 0.902. Best cut off values to diagnose peanut allergy were 4.40 kU/l for FEIA Ara h 2 sIgE and, 7.43 ISU and 8.13 ISU for respectively Ara h 2 and Ara h 6 sIgE in ISAC microarray. Ara h 2 sIgE determined in FEIA and ISAC showed a good correlation (r = 0.88; p < 0.01).

Conclusion

Ara h 6 and Ara h 2 sIgE in multiplex ISAC are both good predictors of clinical peanut allergy in Dutch children, and their performance is comparable to the use of Ara h 2 in singleplex FEIA. The simultaneous measurement of different peanut components using ISAC is an advantage and clinically useful to detect peanut allergic children that are Ara h 2 negative but sensitized to other peanut proteins such as Ara h 6.

Diagnostic accuracy of Ara h 2 for detecting peanut allergy in children

Background

Specific IgE to Ara h 2 is a diagnostic test for peanut allergy which may reduce the need for double‐blind placebo‐controlled food challenges (DBPCFC); however, guidance for using Ara h 2 in place of DBPCFCs has not been validated.

Objective

To prospectively evaluate 1) diagnostic accuracy of previously published Ara h 2 cut‐off levels to diagnose peanut allergy in children and 2) costs.

Methods

A consecutive series of 150 children age 3.5 to 18 years was evaluated in secondary and tertiary settings in the Netherlands. sIgE to Ara h 2 was the index test, and oral peanut ingestion was the reference test. Oral peanut ingestion was home or supervised introduction for Ara h 2 ≤ 0.1, DBPCFC for 0.1–5.0 and open food challenge for ≥5.0. Costs were calculated using financial healthcare data.

Results

A conclusive reference test was performed in 113 children (75%). Sixty‐four children (57%) had peanut allergy, as confirmed by a DBPCFC (27/47) or an open challenge (37/50). Forty‐nine children (43%) were considered peanut‐tolerant after peanut introduction (19/19), a DBPCFC (20/47) or an open challenge (10/50). Area under the curve for Ara h 2 was 0.94 (95% CI 0.90–0.98). The diagnostic flow chart correctly classified 26/26 (100%; 84–100) of children with Ara h 2 ≤ 0.1 as peanut‐tolerant and 34/35 (97%; 83–100) of children with Ara h 2 ≥ 5.0 as peanut‐allergic. At a cut‐off of ≤0.1 and ≥5.0, a sensitivity of respectively 100% (93–100) and 53% (38–67) was observed and a specificity of 53% (38–67) and 98% (87–100). Mean annual costs of the flow chart were estimated as €320‐€636 per patient lower than following national allergy guidelines.

Conclusions

In this diagnostic accuracy study, which did not take into account pretest probability, we have validated previously published Ara h 2 cut‐off levels which are associated with peanut tolerance and allergy.

The Importance of Diet in Predicting the Remission of Urticaria-Determination of Allergen-Specific IgE

Background and Objectives: Different types of food introduced gradually in the diet will expose children to different food allergens, increasing the chance of developing allergic diseases. The aim of our study was to determine if allergen-specific IgE values can influence, depending on the diet, the prediction of remission of urticaria in children. Materials and Methods: This prospective study was conducted in 132 patients diagnosed over two years with urticaria, admitted to "Sf. Maria" Clinical Pediatric Hospital Iaşi. Total IgE assay was performed by ELISA, and determination of specific serum IgE by the CLA System Quanti Scan method (Innogenetics, Heiden, Germany). Data were gathered and statistical analysis was performed using statistical software SPSS, using descriptive and inferential statistics. Results: The determination of specific IgE to food allergens was performed on a total of 132 cases. The values of specific IgE were positive for one or more food allergens in 84 patients (63.64%). The most common allergens involved were: cow's milk in 33.3% cases, egg white in 22.6% cases, and hazelnuts in 11.9% cases. The specific IgE values for the different types of food included in our study had a predictive value for disease remission. Conclusions: The determination of specific IgE confirms the presence of a particular food allergen and may have predictive value for the future development of an allergic manifestation.

ImmunoCAP ISAC in food allergy diagnosis: a systematic review of diagnostic test accuracy

OBJECTIVE

To assess the diagnostic test accuracy of the component-resolved diagnosis device ImmunoCAP ISAC, compared with oral food challenge.

DESIGN

Systematic review reported according to the PRISMA-DTA recommendations.

DATA SOURCES

Medline, Embase and Cochrane Library databases were searched from inception to May 2019 and updated in March 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

We included diagnostic test accuracy studies comparing ISAC component results as the index test with oral food challenge as the reference test, in people of any age suspected of IgE mediated food allergy to milk, egg, peanut, shrimp, hake, apple, peach, kiwi, melon, walnut, hazelnut, wheat or pineapple. Risk of bias was evaluated using the QUADAS-2 tool.

RESULTS

We screened 799 titles and included 11 studies - seven prospective and two retrospective cohort studies, two case-control studies. Included studies evaluated IgE to Gald1 (three studies, 300 participants, 140 with egg allergy), Bosd5 (three studies, 242 participants, 146 with milk allergy) and Arah1 or 2 (seven studies, 546 participants, 346 with peanut allergy). No studies were identified for other ISAC components. Risk of bias was high or unclear mainly due to inadequate blinding. Applicability was of high or unclear concern due to unclear thresholds, inappropriate exclusions and variable populations. Gald1 sensitivity ranged from 58 to 84%, specificity 87%-97%. Bosd5 sensitivity 24%-40%, specificity 94%-95%. Arah1 sensitivity 45%-91%, specificity 41%-93%. Arah2 sensitivity 70%-94%, specificity 75%-95%.

CONCLUSIONS

Diagnostic test accuracy information for ISAC components was only available for milk, egg and peanut. Specificity is generally higher than sensitivity, which contrasts with the performance of skin prick and standard specific IgE tests for diagnosing food allergy. Higher quality information is needed to determine the clinical utility of ISAC for food allergy diagnosis.

SYSTEMATIC REVIEW REGISTRATION

Not registered.

The importance of the 2S albumins for allergenicity and cross-reactivity of peanuts, tree nuts, and sesame seeds

Allergies to peanuts, tree nuts, and sesame seeds are among the most important food-related causes of anaphylaxis. Important clinical questions include: Why is there a variable occurrence of coallergy among these foods and Is this immunologically mediated? The clinical and immunologic data summarized here suggest an immunologic basis for these coallergies that is based on similarities among the 2S albumins. Data from component resolved diagnostics have highlighted the relationship between IgE binding to these allergens and the presence of IgE-mediated food allergy. Furthermore, in vitro and in vivo experiments provide strong evidence that the 2S albumins are the most important allergens in peanuts for inducing an allergic effector response. Although the 2S albumins are diverse, they have a common disulfide-linked core with similar physicochemical properties that make them prime candidates to explain much of the observed coallergy among peanuts, tree nuts, and sesame seeds. The well-established frequency of cashew and pistachio nut coallergy (64%-100%) highlights how the structural similarities among their 2S albumins may account for observed clinical cross-reactivity. A complete understanding of the physicochemical properties of the 2S albumins in peanuts, tree nuts, and sesame seeds will enhance our ability to diagnose, treat, and ultimately prevent these allergies.

Ranking of 10 legumes according to the prevalence of sensitization as a parameter to characterize allergenic proteins

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10 different legumes extracts could be ranked based on the variations in the prevalence of sensitization.

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Variations in the prevalence of sensitization allowed for ranking of 18 different individual legume proteins.

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Ranking can be used to select reference proteins to develop predictive assays for the assessment of the sensitizing potential of novel proteins.

Predicting the allergenicity of novel proteins is challenging due to the absence of validated predictive methods and a well-defined reference set of proteins. The prevalence of sensitization could be a parameter to select reference proteins to characterize allergenic proteins. This study investigated whether the prevalence of sensitization of legume extracts and proteins can indeed be used for this purpose. A random sample of suspected food-allergic patients (n=106) was therefore selected. 10 extracts (processed and non-processed) and 18 individual proteins (2S albumins, 7S and 11S globulins) from black lentil, blue and white lupine, chickpea, faba bean, green lentil, pea, peanut, soybean, and white bean were isolated and the prevalence of sensitization and the intensity of IgE binding were evaluated. The prevalence of sensitization ranged from 5.7 % (faba bean and green lentil) to 14.2 % (peanut). The prevalence of sensitization for individual legume proteins ranged from 0.0 % for albumin 1 (pea) to 15.1 %–17.9 % for Ara h 1, 2, 3, and 6 (peanut). The prevalence of sensitization correlated strongly with the intensity of IgE binding for individual proteins (p < 0.05, ρ = 0.894), for extracts no correlation was found. The discovered ranking can be used to select reference proteins for the development and validation of predictive in vitro or in vivo assays for the assessment of the sensitizing potential.

Component-resolved diagnostics in pet allergy: Current perspectives and future directions

Furry mammals kept as pets are important allergen sources. The prevalence of sensitization to dander from various animals appears to be increasing worldwide. Several mammalian allergens from diverse species and distinct protein families have been characterized, and some are available for component-resolved diagnostics (CRD). This review presents an overview of mammalian aeroallergens, with a focus on cat, dog, and horse allergens. The potential of CRD in fine-tuning the diagnostic workup following traditional methods based on whole- allergen extracts and allergen immunotherapy is discussed. The review highlights the clinical utility of CRD, particularly as a marker/predictor of increased asthma risk and disease severity. Finally, several perspectives of the future implications of CRD are offered in the context of furry animal allergens.

Biomarkers for diagnosis and prediction of therapy responses in allergic diseases and asthma

Modern health care requires a proactive and individualized response to diseases, combining precision diagnosis and personalized treatment. Accordingly, the approach to patients with allergic diseases encompasses novel developments in the area of personalized medicine, disease phenotyping and endotyping, and the development and application of reliable biomarkers. A detailed clinical history and physical examination followed by the detection of IgE immunoreactivity against specific allergens still represents the state of the art. However, nowadays, further emphasis focuses on the optimization of diagnostic and therapeutic standards and a large number of studies have been investigating the biomarkers of allergic diseases, including asthma, atopic dermatitis, allergic rhinitis, food allergy, urticaria and anaphylaxis. Various biomarkers have been developed by omics technologies, some of which lead to a better classification of distinct phenotypes or endotypes. The introduction of biologicals to clinical practice increases the need for biomarkers for patient selection, prediction of outcomes and monitoring, to allow for an adequate choice of the duration of these costly and long‐lasting therapies. Escalating healthcare costs together with questions about the efficacy of the current management of allergic diseases require further development of a biomarker‐driven approach. Here, we review biomarkers in diagnosis and treatment of asthma, atopic dermatitis, allergic rhinitis, viral infections, chronic rhinosinusitis, food allergy, drug hypersensitivity and allergen immunotherapy with a special emphasis on specific IgE, the microbiome and the epithelial barrier. In addition, EAACI guidelines on biologicals are discussed within the perspective of biomarkers.

Peanut allergy diagnosis: A 2020 practice parameter update, systematic review, and GRADE analysis

Given the burden of disease and the consequences of a diagnosis of peanut allergy, it is important that peanut allergy be accurately diagnosed so that an appropriate treatment plan can be developed. However, a test that indicates there is peanut sensitization present (eg, a "positive" test) is not always associated with clinical reactivity. This practice parameter addresses the diagnosis of IgE-mediated peanut allergy, both in children and adults, as pertaining to 3 fundamental questions, and based on the systematic reviews and meta-analyses, makes recommendations for the clinician who is evaluating a patient for peanut allergy. These questions relate to when diagnostic tests should be completed, which diagnostic tests to utilize, and the utility (or lack thereof) of diagnostic testing to predict the severity of a future allergic reaction to peanut.

Accurate Prediction of Peanut Allergy in One-Third of Adults Using a Validated Ara h 2 Cutoff

BACKGROUND

The diagnostic value of peanut components is extensively studied in children, but to a lesser extent in adults with suspected peanut allergy. The use of peanut components in daily practice may reduce the need for double-blind placebo-controlled food challenges (DBPCFCs); however, validation studies are currently lacking.

OBJECTIVE

To evaluate the diagnostic value of (combined) peanut components and validate a previously found Ara h 2 cutoff level with 100% positive predictive value (PPV) in adults with suspected peanut allergy.

METHODS

Adults who underwent a peanut DBPCFC were included: 84 patients from a previous study (2002-2012) and 70 new patients (2012-2019). Specific IgE (sIgE) to peanut extract, Ara h 1, 2, 3, 6, and 8 was measured using ImmunoCAP. Diagnostic value was assessed with an area under the curve (AUC) analysis.

RESULTS

In total, 95 (62%) patients were peanut allergic. sIgE to Ara h 2 and Ara h 6 were the best predictors with an AUC (95% confidence interval) of 0.85 (0.79-0.91) and 0.85 (0.79-0.92), respectively. The Ara h 2 cutoff level with 100% PPV (≥1.75 kU_A/L) was validated in the 70 new patients. Thirty percent of all included patients could be classified correctly as peanut allergic using this validated cutoff level.

CONCLUSION

sIgE to Ara h 2 and Ara h 6 have equally high discriminative ability. Peanut allergy can be predicted accurately in one-third of adults using a validated cutoff level of sIgE to Ara h 2.

Diagnosis of peanut allergy using continuous likelihood ratios

BACKGROUND

Peanut allergy (PA) is associated with an economic and psychological burden on patients and families. Its diagnosis includes tests for peanut specific immunoglobulin E (sIgE), the values of which usually are categorized as positive or negative using a predefined cutoff (usually 0.35 kU/L). With the use of Bayes' theorem, this categorization can be replaced with a continuous interpretation of sIgE, which accounts for the prevalence of PA and history of ingestion.

OBJECTIVE

To evaluate a method for estimating the likelihood ratio (LR) for each value of sIgE by performing a pilot investigation with the results of oral food challenges. The LR could be used to estimate the probability of PA.

METHODS

The outcomes of oral food challenges and serum IgE values from 117 children seen in an allergy clinic between January 2017 and November 2019 were obtained. Polynomial regression of the receiver operation characteristics curve was used to determine an LR for each value of sIgE. Linear regression was used to estimate an LR for each value of sIgE.

RESULTS

sIgE ranged from less than 0.1 kU/L to 35 kU/L. Bayes' theorem and a receiver operation characteristics curve were used to estimate LRs for each value of peanut sIgE. The value of IgE associated with an LR of 1 was 0.22 kU/L, which is comparable to other studies that used a value of 0.35 kU/L to separate positive from negative results.

CONCLUSION

When combined with estimates of pretest probability, this method should permit the development of computerized decision-making algorithms to estimate the probability that a patient has PA.

Peanut allergy diagnosis: Moving from basic to more elegant testing

Peanut allergy (PNA) is an IgE-mediated immune disorder, which merits particular attention due to its impact on the health and quality of life of millions of patients worldwide. PNA tends to develop in early life and resolves in only 20% of peanut-allergic children. It accounts for the majority of severe food-related allergic reactions. An accurate diagnosis of PNA is vital. In this review, we present the approach to the diagnosis of peanut allergy, starting from the history and proceeding to measures of overall sensitization and then to component-resolved diagnostics and oral food challenges as indicated. Additional testing in development includes basophil activation testing and determination of epitopes for peanut-allergic responses. Based on the literature, stepwise approaches and predictive models for diagnosing PNA are also presented.

Accuracy of component-resolved diagnostics in peanut allergy: Systematic literature review and meta-analysis

BACKGROUND

Peanut allergy diagnosis relies on clinical reactivity to peanut supported by detection of specific IgE (sIgE) antibodies. Extract-based sIgE tests have low specificity, so component-resolved diagnostics may complement whole-extract testing.

METHODS

We systematically collected peanut allergen component data in seven databases and studied the diagnostic accuracy of peanut storage proteins (Arah1, 2, 3) and cross-reactive peanut proteins (Arah8 PR-10 and Arah9 lipid transfer protein) through meta-analyses. The systematic literature review included studies employing peanut components and oral food challenge (OFC) as reference standard in patients suspected of peanut allergy. Data for component sIgE at pre-defined detection thresholds were extracted and combined in random-effects bivariate meta-analyses. Risk of bias was assessed as recommended by Cochrane, with two additional quality items of importance for this review.

RESULTS

Nineteen eligible studies presented data suitable for meta-analysis. In cross-sectional pediatric studies, the pooled sensitivity of Arah2-sIgE at 0.35 kU_A /L cutoff was 83.3% [95% CI 75.6, 88.9] and specificity in diagnosing objective peanut allergy was 83.6% [95% CI 77.4, 88.4]. Compared with 0.1 and 1.0 kU_A /L, this threshold provided the best diagnostic accuracy. At 0.35 kU_A /L, Arah1 and Arah3 had comparable specificity (86.0% and 88.0%, respectively) but significantly lower sensitivity compared with Arah2 (37.0% and 39.1%, respectively; P < .05).

CONCLUSION

sIgE to Arah2 can enhance the certainty of diagnosis and reduce the number of OFC necessary to rule out clinical peanut allergy in unclear cases.

Prevalence and natural history of tree nut allergy

OBJECTIVE

Tree nuts are common causes of food-related allergic reactions and anaphylaxis. Resolution of tree nut allergy is thought to be low, yet studies of the natural history of tree nut allergy are limited. This review summarizes the available literature regarding tree nut allergy prevalence and natural history and discusses emerging diagnostic and prognostic developments that will inform clinical management of tree nut allergy.

DATA SOURCES

A comprehensive literature search using PubMed was performed.

STUDY SELECTIONS

Peer-reviewed publications relating to tree nut allergy prevalence, resolution, and diagnosis were selected, and findings were summarized using a narrative approach.

RESULTS

Tree nut allergy prevalence varies by age, region, and food allergy definition, and ranges from less than 1% to approximately 3% worldwide. Reports on the natural history of tree nut allergy data are limited to retrospective clinical data or cross-sectional survey data of self-reported food allergy, with reported resolution ranging from 9% to 14%. Component-resolved diagnostics and basophil activation testing offer the potential to improve the diagnostic accuracy and predicted prognosis of specific tree nut allergy, but studies are limited.

CONCLUSION

Tree nut allergy remains an understudied area of food allergy research with limited region-specific studies based on robust food allergy measures in population cohorts with longitudinal follow-up. This currently limits our understanding of tree nut allergy prognosis.

Investigation of house dust mite induced allergy using logistic regression in West Bengal, India

BACKGROUND

The diagnosis of house dust mite (HDM) allergy based on Skin prick test (SPT) is not accurate, especially in lower risk cases. Our aim is to develop and validate a predictive model to diagnose the HDM allergic symptoms (urticaria, allergic rhinitis, asthma).

METHODS

A forward-step logistic regression model was developed using a data set of 537 patients of West Bengal, India consisting of clinical variables (SPT based on 6 allergens of house dust and house dust mites, total IgE) and demographic characteristics (age, sex, house conditions). The output probability was estimated from the allergic symptoms shown by the patients. We finally prospectively validated a data set of 600 patients.

RESULTS

The gradual inclusion of the variables increased the correlation between observed and predicted probabilities (correlation coefficient (r2) = 0.97). The model development using group-1 showed an accuracy rate of 99%, sensitivity and specificity of 99.7% and 88.6% respectively and the area under the receiver operating characteristics (ROC) curve (AUC) of 99%. The corresponding numbers for the validation of our model with group-2 were 87%, 95.6% and 66% and 86% respectively. The model predicted the probability of symptoms better than SPTs in combination (accuracy rate 0.76-0.80), especially in lower risk cases (probability< 0.8) that are highly difficult to diagnose.

CONCLUSION

This is perhaps the first attempt to model the outcome of HDM allergy in terms of symptoms, which could open up an alternative but highly efficient way for accurate diagnosis of HDM allergy enhancing the efficiency of immunotherapy.

Screening of Nanobody Specific for Peanut Major Allergen Ara h 3 by Phage Display

Peanut allergy is a major health problem worldwide. Detection of food allergens is a critical aspect of food safety. The VHH domain of single chain antibody from camelids, also known as nanobody (Nb), showed its advantages in the development of biosensors because of its high stability, small molecular size, and ease of production. However, no nanobody specific to peanut allergens has been developed. In this study, we constructed a library with random triplets (NNK) in its CDR regions of a camel nanobody backbone. We screened the library with peanut allergy Ara h 3 and obtained several candidate nanobodies. One of the promising nanobodies, Nb16 was further biochemical characterization by gel filtration, isothermal titration calorimetry (ITC), cocrystallization, and Western blot in terms of its interaction with Ara h 3. Nb16 specifically binds to peanut major allergen Ara h 3 with a dissociation constant of 400 nM. Furthermore, we obtained the Ara h 3-Nb16 complex crystals. Structure analysis shows the packing mode is completely different between the Ara h 3-Nb16 complex crystal and the native Ara h 3 crystal. Structural determination of Ara h 3-Nb16 will provide the necessary information to understand the allergenicity of this important peanut allergen. The nanobody Nb16 may have application in the development of biosensors for peanut allergen detection.

Ara h 7 isoforms share many linear epitopes: Are 3D epitopes crucial to elucidate divergent abilities?

Background

The peanut allergens Ara h 2, h 6, and h 7 are potent allergens and can trigger severe reactions. Ara h 7 consists of three isoforms differing in their ability to induce basophil degranulation, whereas the ability of Ara h 7.0201 is comparable to Ara h 2 and 6 as shown in previous literature.

Objective

To identify linear epitopes of Ara h 7.0101, Ara h 7.0201 and Ara h 7.0301 recognized by IgE and IgG4 from patients sensitized to Ara h 7 and to investigate their potential to elucidate divergent abilities of the Ara h 7 isoforms in inducing basophil activation.

Methods

Linear epitopes recognized by IgE and IgG4 were mapped by peptide microarray analysis containing 15‐mer peptides of Ara h 2.0201, 6, 7.0101, 7.0201 and 7.0301 and 39 peanut allergic patients sensitized to Ara h 7 (discovery). For validation, 20‐mer peptides containing the minimal epitope and surrounding amino acids were incubated with 25 sensitized patients and 10 controls (validation).

Results

Three out of 14 linear epitopes were unique for each isoform (Ara h 7.0101: aa 97‐109; Ara h 7.0201: aa 122‐133; Ara h 7.0301: aa 65‐74) but scarcely recognized by IgE. The main linear IgE epitope (aa 51‐57) located in the long flexible loop of all Ara h 7 isoforms was bound by antibodies from 31% of the patients (discovery and validation cohort). Regarding IgG4, 55% of the patients recognized an epitope present on all isoforms (aa 55‐65), whereas epitope aa 129‐137, only present on Ara h 7.0101/0.0301, was recognized by 38% of the patients. Recognition was highly individual, although 20% of the patients recognized any linear epitope neither by IgE nor by IgG4 despite a low mean z‐score of ≥ 1.7. Remarkably, only 50% of the patients recognized one or more epitopes by IgE.

Conclusion & Clinical Relevance

Ara h 7 isoforms share many linear epitopes being easily accessible for antibody binding. Unique epitopes, essential to elucidate divergent potencies, were scarcely recognized, suggesting a crucial involvement of conformational epitopes.

Gender, prick test size and rAra h 2 sIgE level may predict the eliciting dose in patients with peanut allergy: Evidence from the Mirabel survey

BACKGROUND

Peanut allergy management is based on active avoidance and access to emergency treatment including self-injectable adrenaline. Knowing the dose at which a patient is likely to react is crucial for risk assessment and could significantly improve management by integrating a personalized approach.

OBJECTIVE

To develop a threshold dose distribution curve model from routinely collected data.

METHODS

The MIRABEL survey is an observational study of 785 patients with peanut allergy/sensitization conducted in France, Belgium and Luxemburg. The current analysis included the 238 participants for whom medical and oral food challenge data were available. Several statistical models (Kaplan-Meier, Cox model, Weibull and Lognormal with predictive factors, basic Weibull and Lognormal) were compared to select the best model and predictive factor combination associated with the threshold doses. Inferences were made with a Bayesian approach.

RESULTS

Patients were mainly children (mean age: 9 years [IQR: 6-11]; 87% < 16 years) and males (62%). Median Ara h2 s IgE was of 8kUA/L [IQR: 1-55] and median skin prick test size of 10 mm [IQR: 7-13]. OFC was positive in 204 patients (86%). The median threshold dose was of 67 mg of peanut protein [IQR: 16-244]. The dose at which 1% of the patients are likely to react with objective symptoms was 0.26 [0.03; 2.24] mg of peanut protein. Gender, size of the skin prick test (SPT) and Ara h 2 specific IgE level had a significant impact on the threshold dose distribution curve. The Cox model was the most effective to predict threshold doses with this combination of factors. Girls react to lower doses than boys with a beta coefficient associated to the risk and a 95% credible interval of 0.44 [0.04; 0.77]. The higher the size of the SPT and the Ara h 2 specific IgE level are, the higher the risk of reacting to a small amount of peanut, with beta coefficients associated to the risk and 95% credible intervals of 0.05 [0.02; 0.08] and 0.01 [0.01; 0.02], respectively.

CONCLUSION AND CLINICAL RELEVANCE

According to the model, routinely collected data could be used to estimate the threshold dose. The consequences could be the identification of high-risk patients who are susceptible to react to small amounts of peanut and a personalized management of peanut allergy integrating the risk of allergic reaction. Limitations of this study are that assessors of OFC outcome were aware of SPT and Arah2 results, and a further validation study is required to confirm the predictive value of these parameters.

IgE testing can predict food allergy status in patients with moderate to severe atopic dermatitis

BACKGROUND

Diagnosing food allergy in patients with atopic dermatitis (AD) is complicated by their high rate of asymptomatic sensitization to foods, which can lead to misdiagnosis and unnecessary food avoidance.

OBJECTIVE

We sought to determine whether food-specific (sIgE) or component immunoglobulin (Ig) E levels could predict allergic status in patients with moderate to severe AD and elevated total IgE.

METHODS

Seventy-eight children (median age, 10.7 years) with moderate to severe AD were assessed for a history of clinical reactivity to milk, egg, peanut, wheat, and soy. The IgE levels for each food and its components were determined by ImmunoCAP. The level and pattern of IgE reactivity to each food and its components, and their ratio to total IgE, were compared between subjects who were allergic and tolerant to each food.

RESULTS

Ninety-one percent of subjects were sensitized, and 51% reported allergic reactivity to at least 1 of the 5 most common food allergens. Allergy to milk, egg, and peanut were most common, and IgE levels to each of these foods were significantly higher in the allergic group. Component IgEs most associated with milk, egg, and peanut allergy were Bos d8, Gal d1, and Ara h2, respectively. The ratio of sIgE to total IgE offered no advantage to sIgE alone in predicting allergy.

CONCLUSION

Specific IgE levels and the pattern of IgE reactivity to food components can distinguish AD subjects allergic vs tolerant to the major food allergens and may therefore be helpful in guiding the clinical management of these patients.

Ratios of specific IgG4 over IgE antibodies do not improve prediction of peanut allergy nor of its severity compared to specific IgE alone

Background

IgG₄ antibodies have been suggested to play a protective role in the translation of peanut sensitization into peanut allergy. Whether they have added value as diagnostic read‐out has not yet been reported.

Objective

To evaluate whether (a) peanut‐specific IgG, IgG₄ and/or IgA antibodies are associated with tolerance and/or less severe reactions and (b) they can improve IgE‐based diagnostic tests.

Methods

Sera of 137 patients with challenge‐proven peanut allergy and of 25 subjects that tolerated peanut, both with known IgE profiles to peanut extract and five individual peanut allergens, were analyzed for specific IgG and IgG₄. Antibody levels and ratios thereof were associated with challenge outcome including symptom severity grades. For comparison of the discriminative performance, receiver operating characteristic curve (ROC) analysis was used.

Results

IgE against Ara h 2 was significantly higher in allergic than in tolerant patients and associated with severity of reactions (P < 0.001) with substantial diagnostic capability (AUC 0.91, 95%CI 0.87‐0.96 and 0.80, 95%CI 0.73‐0.87, respectively). IgG and IgG₄ were also positively associated albeit significantly weaker (AUCs from 0.65 to 0.72). On the other hand, ratios of IgG and IgG₄ over IgE were greater in patients that were tolerant or had mild symptoms as compared to severe patients but they did not predict challenge outcomes better than IgE alone (AUCs from 0.54 to 0.89).

Conclusion

IgE against Ara h 2 is the best biomarker for predicting peanut challenge outcomes including severity and IgG and IgG₄ antibody ratios over IgE do not improve these outcomes.

Development of a tool predicting severity of allergic reaction during peanut challenge

BACKGROUND

Reliable prognostic markers for predicting severity of allergic reactions during oral food challenges (OFCs) have not been established.

OBJECTIVE

To develop a predictive algorithm of a food challenge severity score (CSS) to identify those at higher risk for severe reactions to a standardized peanut OFC.

METHODS

Medical history and allergy test results were obtained for 120 peanut allergic participants who underwent double-blind, placebo-controlled food challenges. Reactions were assigned a CSS between 1 and 6 based on cumulative tolerated dose and a severity clinical indicator. Demographic characteristics, clinical features, peanut component IgE values, and a basophil activation marker were considered in a multistep analysis to derive a flexible decision rule to understand risk during peanut of OFC.

RESULTS

A total of 18.3% participants had a severe reaction (CSS >4). The decision rule identified the following 3 variables (in order of importance) as predictors of reaction severity: ratio of percentage of CD63^hi stimulation with peanut to percentage of CD63^hi anti-IgE (CD63 ratio), history of exercise-induced asthma, and ratio of forced expiratory volume in 1 second to forced vital capacity (FEV₁/FVC) ratio. The CD63 ratio alone was a strong predictor of CSS (P < .001).

CONCLUSION

The CSS is a novel tool that combines dose thresholds and allergic reactions to understand risks associated with peanut OFCs. Laboratory values (CD63 ratio), along with clinical variables (exercise-induced asthma and FEV₁/FVC ratio) contribute to the predictive ability of the severity of reaction to peanut OFCs. Further testing of this decision rule is needed in a larger external data source before it can be considered outside research settings.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02103270.

Food allergy

Food allergies manifest in a variety of clinical conditions within the gastrointestinal tract, skin and lungs, with the most dramatic and sometimes fatal manifestation being anaphylactic shock. Major progress has been made in basic, translational and clinical research, leading to a better understanding of the underlying immunological mechanisms that lead to the breakdown of clinical and immunological tolerance against food antigens, which can result in either immunoglobulin E (IgE)-mediated reactions or non-IgE-mediated reactions. Lifestyle factors, dietary habits and maternal-neonatal interactions play a pivotal part in triggering the onset of food allergies, including qualitative and quantitative composition of the microbiota. These factors seem to have the greatest influence early in life, an observation that has led to the generation of hypotheses to explain the food allergy epidemic, including the dual-allergen exposure hypothesis. These hypotheses have fuelled research in preventive strategies that seek to establish desensitization to allergens and/or tolerance to allergens in affected individuals. Allergen-nonspecific therapeutic strategies have also been investigated in a number of clinical trials, which will eventually improve the treatment options for patients with food allergy.