Understanding immunological origins of atopic dermatitis through multi‐omic analysis
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 longit...
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| Veröffentlicht in: | Pediatric allergy and immunology 2022-06, Vol.33 (6), p.e13817-n/a |
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| creator | Beheshti, Ramin Halstead, Scott McKeone, Daniel Hicks, Steven D. |
| description | 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 |
| doi_str_mv | 10.1111/pai.13817 |
| format | Article |
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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 (X2 = 32.47, p = .006).
Conclusion
Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro‐inflammatory environment.</description><identifier>ISSN: 0905-6157</identifier><identifier>EISSN: 1399-3038</identifier><identifier>DOI: 10.1111/pai.13817</identifier><language>eng</language><publisher>Montpellier: Wiley Subscription Services, Inc</publisher><subject>allergy ; Atopic dermatitis ; atopy ; biomarkers ; Breast feeding ; cytokines ; Demography ; Dermatitis ; Eczema ; Environmental factors ; Gestational age ; Infants ; Inflammation ; Interleukin 6 ; Medical records ; microbiome ; Microbiomes ; miRNA ; oropharynx ; Pets ; Proteobacteria ; Saliva ; Surveys</subject><ispartof>Pediatric allergy and immunology, 2022-06, Vol.33 (6), p.e13817-n/a</ispartof><rights>2022 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.</rights><rights>Copyright © 2022 John Wiley & Sons A/S</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2607-ed70a111520afe004c2bb22f2618566a6bdc4bb05c24c0f28c50dd26056e86ab3</citedby><cites>FETCH-LOGICAL-c2607-ed70a111520afe004c2bb22f2618566a6bdc4bb05c24c0f28c50dd26056e86ab3</cites><orcidid>0000-0002-0817-844X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fpai.13817$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fpai.13817$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,27928,27929,45578,45579</link.rule.ids></links><search><creatorcontrib>Beheshti, Ramin</creatorcontrib><creatorcontrib>Halstead, Scott</creatorcontrib><creatorcontrib>McKeone, Daniel</creatorcontrib><creatorcontrib>Hicks, Steven D.</creatorcontrib><title>Understanding immunological origins of atopic dermatitis through multi‐omic analysis</title><title>Pediatric allergy and immunology</title><description>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 (X2 = 32.47, p = .006).
Conclusion
Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro‐inflammatory environment.</description><subject>allergy</subject><subject>Atopic dermatitis</subject><subject>atopy</subject><subject>biomarkers</subject><subject>Breast feeding</subject><subject>cytokines</subject><subject>Demography</subject><subject>Dermatitis</subject><subject>Eczema</subject><subject>Environmental factors</subject><subject>Gestational age</subject><subject>Infants</subject><subject>Inflammation</subject><subject>Interleukin 6</subject><subject>Medical records</subject><subject>microbiome</subject><subject>Microbiomes</subject><subject>miRNA</subject><subject>oropharynx</subject><subject>Pets</subject><subject>Proteobacteria</subject><subject>Saliva</subject><subject>Surveys</subject><issn>0905-6157</issn><issn>1399-3038</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp10L1OwzAQB3ALgUQpDLxBJBYYUs5O7CRjVfFRqRIMlNVyHCd15cTFToS68Qg8I0-CaZiQuOWG-93p9EfoEsMMh7rdCT3DSY6zIzTBSVHECST5MZpAATRmmGan6Mz7LQDOEoYn6HXdVcr5XnSV7ppIt-3QWWMbLYWJrNON7nxk60j0dqdlFGwret1rH_UbZ4dmE7WD6fXXx6dtw1x0wuy99ufopBbGq4vfPkXr-7uXxWO8enpYLuarWBIGWayqDER4mxIQtQJIJSlLQmrCcE4ZE6ysZFqWQCVJJdQklxSqKqxSpnImymSKrse7O2ffBuV73movlTGiU3bwnLAcpylhLAn06g_d2sGFfw8KCkKzAgd1MyrprPdO1XzndCvcnmPgPwnzkDA_JBzs7WjftVH7_yF_ni_HjW8uNX6E</recordid><startdate>202206</startdate><enddate>202206</enddate><creator>Beheshti, Ramin</creator><creator>Halstead, Scott</creator><creator>McKeone, Daniel</creator><creator>Hicks, Steven D.</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T5</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0817-844X</orcidid></search><sort><creationdate>202206</creationdate><title>Understanding immunological origins of atopic dermatitis through multi‐omic analysis</title><author>Beheshti, Ramin ; Halstead, Scott ; McKeone, Daniel ; Hicks, Steven D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2607-ed70a111520afe004c2bb22f2618566a6bdc4bb05c24c0f28c50dd26056e86ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>allergy</topic><topic>Atopic dermatitis</topic><topic>atopy</topic><topic>biomarkers</topic><topic>Breast feeding</topic><topic>cytokines</topic><topic>Demography</topic><topic>Dermatitis</topic><topic>Eczema</topic><topic>Environmental factors</topic><topic>Gestational age</topic><topic>Infants</topic><topic>Inflammation</topic><topic>Interleukin 6</topic><topic>Medical records</topic><topic>microbiome</topic><topic>Microbiomes</topic><topic>miRNA</topic><topic>oropharynx</topic><topic>Pets</topic><topic>Proteobacteria</topic><topic>Saliva</topic><topic>Surveys</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Beheshti, Ramin</creatorcontrib><creatorcontrib>Halstead, Scott</creatorcontrib><creatorcontrib>McKeone, Daniel</creatorcontrib><creatorcontrib>Hicks, Steven D.</creatorcontrib><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Pediatric allergy and immunology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Beheshti, Ramin</au><au>Halstead, Scott</au><au>McKeone, Daniel</au><au>Hicks, Steven D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Understanding immunological origins of atopic dermatitis through multi‐omic analysis</atitle><jtitle>Pediatric allergy and immunology</jtitle><date>2022-06</date><risdate>2022</risdate><volume>33</volume><issue>6</issue><spage>e13817</spage><epage>n/a</epage><pages>e13817-n/a</pages><issn>0905-6157</issn><eissn>1399-3038</eissn><abstract>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 (X2 = 32.47, p = .006).
Conclusion
Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro‐inflammatory environment.</abstract><cop>Montpellier</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/pai.13817</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-0817-844X</orcidid></addata></record> |
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| source | Wiley Online Library - AutoHoldings Journals |
| subjects | allergy Atopic dermatitis atopy biomarkers Breast feeding cytokines Demography Dermatitis Eczema Environmental factors Gestational age Infants Inflammation Interleukin 6 Medical records microbiome Microbiomes miRNA oropharynx Pets Proteobacteria Saliva Surveys |
| title | Understanding immunological origins of atopic dermatitis through multi‐omic analysis |
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