Is there a Role for Sensitization in Predicting Severity? Ronald van Ree Academic Medical Center University of Amsterdam
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1 Is there a Role for Sensitization in Predicting Severity? Ronald van Ree Academic Medical Center University of Amsterdam
2 A journey into the past, before this happened
3 2006
4 CRD using four purified apple allergens: A European study on apple allergy 1. Birch-pollen cross-reactive allergen Mal d 1 2. Mal d 2 3. Lipid transfer protein (LTP): true food allergen 4. Mal d 4 The Netherlands Austria Italy Spain Frequency positive RAST (> 1.0 IU/ml) nmal d 1 rmal d 2 nmal d 3 rmal d 4 Frequency positive RAST (> 1.0 IU/ml) nmal d 1 rmal d 2 nmal d 3 rmal d 4 Frequency positive RAST (> 1.0 IU/ml) nmal d 1 rmal d 2 nmal d 3 rmal d 4 Frequency positive RAST (> 1.0 IU/ml) nmal d 1 rmal d 2 nmal d 3 rmal d 4 CRD reveals a clear geographic difference. So what? M Fernandez Rivas et al. J Allergy Clin Immunol 2006 Aug;118(2):481-8.
5 Only patients with IgE antibodies against the true food allergen ( ) have severe systemic symptoms (U: generalized urticaria / AX: anaphylaxis) The risk is for severe food allergy increased by around 8-fold Likely explanation: resistance to gastric digestion 0 NL A I E OAS CU DIG RC ASTHMA U AX SHOCK A positive test to apple extract does not give this level of discrimination.
6 2007
7 A moment of reflection: Where was the SAFE project placed historically? How did we get to ifaam?
8 EU FOOD ALLERGY FUNDING LANDSCAPE FP Allergentest.... FAIR FAREDAT..
9 EU FOOD ALLERGY FUNDING LANDSCAPE FP Allergentest FAIR FAREDAT Molecular allergology track Application of allergen molecules to improve diagnostic tests and identify biomarkers for clinical phenotypes (severity markers). INNOVATIVE DIAGNOSTICS IMPROVED RISK PROFILING
10 EU FOOD ALLERGY FUNDING LANDSCAPE FP Allergentest A long-term vision to build and sustain a multidisciplinary/stakeholder network in food allergy research! FAIR FAREDAT
11 2013: seven years after the apple story KIWI PEANUT HAZELNUT
12
13 Kiwifruit allergy across Europe: Clinical manifestation and IgE recognition patterns to kiwifruit allergens. Thuy-My Le et al. J Allergy Clin Immunol. 2013;131(1): % CI B P value OR Lower Upper Sex Age of onset >5 y Kiwifruit monoallergy Birch pollen allergy Grass pollen allergy Any pollen allergy Living in Iceland Act d 1 (actinidin) 0.35 kua/l 1.74 < Act d 8 (PR-10) 0.35 kua/l Act d 9 (profilin) 0.35 kua/l Act d 10 (nsltp) 0.35 kua/l a deadly combination
14 Eller E, Bindslev-Jensen C Allergy 2013 Feb;68(2): * * Severity grading according to Sampson (here: tolerant/grade I/II vs grade IV/V) Although not part of EuroPrevall but of OdensePrevall and he silently sneaked out of ifaam I still like him and he is part of the European Food Allergy Research family!
15 Laury J.N. Masthoff et al. J Allergy Clin Immunol, Volume 132, Issue 2, 2013, Cor a 9 Cor a 1 Prediction of severe (systemic) symptoms in DBPCFC is best with Cor a 9 and 14
16 Analysis of EuroPrevall outpatient clinic survey in ifaam An example: hazelnut allergy, sensitization and severity
17 Hazelnut allergic patients from EuroPrevall, analyzed in ifaam symptoms mild moderate severe Negative association with severity Positive association with severity Positive association with severity
18 Risk factors and biomarkers associated with severe hazelnut allergy (reported). EuroPrevall outpatient clinic survey.
19
20 Univariate analyses on challenge-associated symptoms gave very similar results. negative association (protection) pollen allergy Cor a 1 sensitization positive association (risk) atopic dermatitis (ever) Cor a 9 and Cor a 14 sensitization walnut sensitization
21 Prediction of severity during DBPCFC with hazelnut AUC SPT 0.72 Single molecule: Cor a 1 sensitization 0.73 Single molecule: Cor a 9 sensitization 0.70 Single molecule: Cor a 14 sensitization 0.71 Model 1: Cor a 1 sensitization + Cor a 9 sensitization 0.76 Model 2: AD (ever) + pollen allergy (reported/matching IgE) 0.75 Model 3: Model 2 + Cor a 14 sensitization 0.86 Model 4: Model 3 + walnut sensitization 0.91 sensitization or history alone all give very similar AUCs models combining history and sensitization give a significant improvement
22 Probability of a severe allergic reaction to hazelnuts Models can be expressed in formulas: Model 1: hazelnut allergens Cor a 1 and Cor a 9 1/(1 + (ee^ ( (Cor a ) + (Cor a ) ) ) ) Model 2: Clinical characteristics 1/(1 + (ee^ ( (atopic dermatitis 1.699) + (pollen allergy 2.076) ) ) ) Model 3: Clinical characteristics + sige against Cor a 14 1/(1 + (ee^ ( (atopic dermatitis 2.290) + (pollen allergy 2.862) + (Cor a ) ) ) ) Model 4: Clinical characteristics + sige against Cor a 14 and walnut 1/(1 + (ee^ ( (atopic dermatitis 2.574) + (pollen allergy 3.005) + Cor a Walnut ) ) ) Diagnostic performance Models including CRD are particularly good in excluding a risk of severe reactions
23 Some (fictional) examples in the different models
24 Model 1 (CRD only) Three patients: 1) Pure PR10 50 ku/l Cor a 1 2) Pure storage proteins 10 ku/l Cor a 9 3) Mixed profile 50 ku/l Cor a 1 10 ku/l Cor a 9 Pure PR10: Pure storage: Mixed profile: 1 1+ ee ^ = ee ^ = = ee^
25 Model 2 (clinical history only) Four patients: 1) atopic dermatitis + / pollen allergy + 2) atopic dermatitis + / pollen allergy 3) atopic dermatitis - / pollen allergy + 4) atopic dermatitis - / pollen allergy AD+/PA+: AD+/PA-: AD-/PA+: AD-/PA-: 1 1+ ee^ = ee^ = = ee ^ ee^ =
26 Model 4 (clinical history + CRD + extract IgE) Four patients: 1) AD+/PA-/Cor a 14+ (10kU/L)/walnut+ (10kU/L) 2) AD+/PA-/Cor a 14+ (10kU/L)/walnut - (0kU/L) 3) AD+/PA+/Cor a 14+ (10kU/L)/walnut+ (10kU/L) 4) AD+/PA+/Cor a 14+ (10kU/L)/walnut- (0kU/L) AD+/PA-/Cor a 14+/walnut+: AD+/PA-/Cor a 14+/walnut-: AD+/PA+/Cor a 14+/walnut+: AD+/PA+/Cor a 14+/walnut-: 1 = ee^ = ee^ = ee^ = ee^
27 Conclusion Is there a role for sensitization in predicting severity? YES In particular molecular allergology has moved the field forward with respect to assessing the risk of severe reactions It will be worthwhile to further evaluate the added value of algorithms combining clinical parameters and CRD.
28 Acknowledgements EU funding from FP4-FP7, in particular for EuroPrevall and ifaam. All collaborators, especially the clinical centers in the EuroPrevall and ifaam consortia and all patients volunteering in these studies. In particular: Clare Mills, Montserrat Fernandez-Rivas, Barbara Ballmer, Jonas Lidholm, Stefan Vieths, Karin Hoffmann-Sommergruber, Carsten Bindslev Jensen, Lars Poulsen, Serge Versteeg, Laurian Jongejan, Koos Zwinderman, Mareen Datema.
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