An Exploration of the Associations Between Gut and Serum Immunoglobulin A in Infancy and Asthma in Childhood
Notice bibliographique
Résumé
Introduction Early immune maturation and gut microbial composition have a clear impact on the development of asthma and atopy in children. There is a large body of evidence on the association between immunoglobulin A (IgA), asthma, and other atopic diseases. Low secretory Immunoglobulin A (sIgA) (mucosal) levels in infancy have been associated with the development of asthma and atopic disease in childhood. As well, absence of serum IgA is associated with increased risk for asthma. Serum IgA levels have also been shown to be increased in those with food sensitization, despite the levels being normal for their age. In this thesis, we determined if lower levels of the primary gut mucosal immunoglobulin (sIgA) during infancy were associated with the development of asthma and/or wheeze in a large prospective, normal birth cohort. In another cohort from a health administrative database, we determined associations between serum IgA during in relationship to Emergency Department (ED) visits for asthma and/or wheeze (AW) in childhood. Objectives This thesis aims to determine the relationships between fecal secretory immunoglobulin A and childhood AW (Study 1) and serum IgA and childhood emergency department visits for AW (Study 2). The objective of study 1 was to determine whether infants with low fecal sIgA (vs normal-high) levels in the first few months of life have increased risk for development AW. Study 2 was developed to determine if low serum IgA children is a useful biomarker for future ED visits for AW. Methods In study 1, 951 infants from the CHILD study sites, Vancouver, Edmonton and Winnipeg were included based on availability of stool samples. A 3-category variable was used: breastfed (any fecal sIgA level), formula fed with low sIgA levels (lowest tertile) and formula fed with normal-high fecal sIgA levels (highest 2 tertiles). Logistic regression models determined the association (Odds Ratio, OR) between low or normal to high fecal sIgA levels in non-breastfed infants and child AW in comparison to breastfed infants, adjusting for confounding factors identified based on a directed acyclic graph to determine the effect of fecal sIgA levels on childhood AW. In study 2, anonymized administrative health data of 9,938 children who had serum IgA levels assessed when they were <=3 years of age between April 1, 2013 and June 30, 2018 was obtained for analysis from Alberta Health Services (AHS) (Alberta, Canada). Multiple logistic regression models determined the association (Odds Ratio, OR) between normal to high serum IgA (top two tertiles compared to the lowest tertile) and child ED visits for AW adjusting for covariates identified by directed acyclic graph. Results In study 1, when compared to breastfed infants, formula fed infants with low fecal sIgA levels had 2.20 times the odds of having a diagnosis of asthma in the first three years of life (OR: 2.13; 95%CI: 1.03, 4.43) when controlling for confounding factors. Formula fed infants with normal to high fecal sIgA were at increased risk for atopic AW at age 1-3 years (OR: 5.45; 95%CI: 1.69, 17.31) compared to their breastfeed counterparts. In study 2, when compared to infants with low serum IgA levels, infants with normal-high serum IgA levels (ages 1-2) had an adjusted OR of having an ED visit for AW of 1.21 (95%CI: 1.00, 1.46), controlling for confounding factors. Those with normal-high levels (from 2-3 years) also had significantly increased odds of atopic AW (adjusted OR: 1.79 (95%CI: 1.03, 3.09) when compared to those without. Conclusion Low levels of infant produced fecal sIgA was associated with increased odds of asthma, whereas normal to high levels were associated with increased odds of atopic AW in comparison to breastfed infants. Normal-high levels of serum IgA in the first 3 years of life appear to be associated with ED visits for AW and atopic AW from 1 until age 3. Further studies are needed to define the relationships between, sIgA, serum IgA, and asthma and atopic sensitization which may provide new insight into the development of respiratory disease and atopic illness in childhood. Overall, both serum IgA and secretory IgA may be important biomarkers to aid in early identification and treatment of those prone to develop atopic diseases like asthma.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».