Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: The pathophysiology of atopic dermatitis (AD) is multifactorial, impacted by individual medical, demographic, environmental, and immunologic factors. This study used multi-omic analyses to assess how host and microbial factors could contribute to infant AD development.
Methods: This longitudinal cohort study included 129 term infants, identified as AD (n = 37) or non-AD (n = 92) using the Infant Feeding Practices-II survey and review of medical records. Standardized surveys were used to assess medical and demographic traits (gestational age, sex, race, maternal AD, and atopy family history), and environmental exposures (delivery method, maternal tobacco use, pets, breastfeeding duration, and timing of solid food introduction). Saliva was collected at 6 months for multi-omic assessment of cytokines, microRNAs, mRNAs, and the microbiome. The contribution of each factor to AD status was assessed with logistic regression.
Results: Medical, demographic, and environmental factors did not differ between AD and non-AD infants. Five "omic" factors (IL-8/IL-6, miR-375-3p, miR-21-5p, bacterial diversity, and Proteobacteria) differed between groups (p < .05). The severity of AD was positively associated with levels of miR-375-3p (R = .17, p = .049) and Proteobacteria (R = .22, p = .011), and negatively associated with levels of miR-21-5p (R = .20, p = .022). Multi-omic features accounted for 17% of variance between groups, significantly improving an AD risk model employing medical, demographic, and environmental factors (X = 32.47, p = .006).
Conclusion: Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro-inflammatory environment.
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http://dx.doi.org/10.1111/pai.13817 | DOI Listing |