Related Experiment Video
Updated: Jan 24, 2026
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Clinical factors associated with peanut allergy in a high-risk infant cohort
Scott H Sicherer1, Robert A Wood2, Tamara T Perry3
1Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York.
Insights
Early prognostication of peanut allergy (PNA) is possible. Key predictors in high-risk infants include lack of breastfeeding, younger age, and higher peanut-specific IgE levels, particularly Ara h2.
Area of Science:
- Allergy and Immunology
- Pediatric Allergy
- Clinical Research
Background:
- Prognostication of peanut allergy (PNA) is crucial for timely interventions in infants.
- This study focused on infants aged 3-15 months with suspected egg/milk allergy, atopic dermatitis (AD), and positive egg/milk skin prick tests (SPT), but no known PNA.
Purpose of the Study:
- To identify baseline parameters predicting the development of PNA in a high-risk infant cohort.
- To develop a predictive model for PNA using early clinical and serologic markers.
Main Methods:
- A cohort of 511 infants was followed for a median of 7.3 years to determine PNA development.
- Univariate and stepwise multiple logistic regression analyses were used to identify prognostic factors.
- Data were stratified by PNA status and randomly assigned to development and validation datasets.
Main Results:
- 40.1% of participants developed PNA.
- Factors associated with PNA included younger age, increased AD severity, larger egg and peanut SPTs, higher specific IgE levels (peanut, Ara h1-h3), and increased peanut consumption during pregnancy/lactation.
- A multivariate model identified younger age, lack of breastfeeding, and greater peanut-specific IgE (especially Ara h2) as significant predictors.
Conclusions:
- Lack of breastfeeding, younger age at enrollment, and elevated peanut-specific IgE (Ara h2) are key prognostic factors for PNA in high-risk infants.
- The developed predictive model demonstrated good accuracy (AUC=0.83) in both development and validation datasets.
- These findings can aid in early risk stratification and intervention for peanut allergy.
Background:
Prognostication of peanut allergy (PNA) is relevant for early interventions. We aimed to determine baseline parameters associated with the development of PNA in 3- to 15-month-olds with likely egg and/or milk allergy, and/or moderate to severe atopic dermatitis (AD) and a positive egg/milk skin prick test (SPT), but no known PNA.
Methods:
The primary endpoint was PNA [confirmed/convincing diagnosis or last classified as serologic PNA (<2 years, ≥5 kUA/L, otherwise ≥14 kUA/L, peanut IgE)] among 511 participants (median follow-up, 7.3 years). Associations were explored with univariate logistic regression; factors with P < 0.15 were analyzed by stepwise multiple logistic regression, using data stratified by PNA status and randomly assigned to development and validation datasets.
Results:
205/511 (40.1%) had PNA. Univariate factors associated with PNA (P < 0.01) included increased AD severity, larger egg and peanut SPT, greater egg, milk, peanut, Ara h1-h3 IgE, higher peanut IgG and IgG4, and increased pregnancy peanut consumption. P-values were between 0.01 and 0.05 for younger age, non-white race, lack of breastfeeding, and increased lactation peanut consumption. Using a development dataset, the multivariate model identified younger age at enrollment, greater peanut and Ara h2 IgE, and lack of breastfeeding as prognosticators. The final model predicted 79% in the development and 75% in the validation dataset (AUC = 0.83 for both). Models using stricter or less strict PNA criteria both found Ara h2 as predictive.
Conclusions:
Key factors associated with PNA in this high-risk population included lack of breastfeeding, age, and greater Ara h2 and peanut-specific IgE, which can be used to prognosticate outcomes.
More Related Videos
09:44RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem
Published on: December 21, 2015
19:15Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Related Concept Videos
01:26Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
01:12Relative Risk
02:16Transcription Factors
01:29Drug Dosing: Infants and Children
04:01Factors Affecting Solubility
02:35Transcription Elongation Factors
The transcription elongation is regulated via pausing of RNA polymerase on several occasions during transcription. In bacteria, these halts are necessary because the transcription of DNA into mRNA is coupled to the translation of that mRNA...