Explore the genetic exposure to alopecia areata
Background Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further in...
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| Veröffentlicht in: | Skin research and technology 2024-08, Vol.30 (8), p.e13874-n/a |
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| creator | Peng, Shaoyi Yang, Yang Man, Yilong Long, Dianfei Wang, Lei Li, Kaiyuan Liu, Peng |
| description | Background
Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation.
Methods
This study employed Mendelian randomization (MR), utilizing data from genome‐wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR‐Egger regression intercept test, MR‐PRESSO global test, and leave‐one‐out analysis, to assess the robustness of the results.
Results
MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75–0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values |
| doi_str_mv | 10.1111/srt.13874 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11291861</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3086957910</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3344-2eb9ea8ca79c81376b37bb620cae5cfd1d350686090b330e9d8cf26cbdce350b3</originalsourceid><addsrcrecordid>eNp1kU9Lw0AQxRdRbK0e_AIS8KKHtLvZZJM9iZT6BwRBK3hbNptJm5Jm426i7bd3a2pRwbkMzPx4vJmH0CnBQ-JqZE0zJDSJwz3UJwxjHych20d9zDH34yh47aEjaxcY44gTeoh6lOOEObKPRpNVXWoDXjMHbwYVNIXyYFVr226G2pOlrkEV0pMGZCOP0UEuSwsn2z5ALzeT6fjOf3i8vR9fP_iK0jD0A0g5yETJmKuE0JilNE5TFmAlIVJ5RjIaYZYw5zClFAPPEpUHTKWZArdJ6QBddbp1my7BTavGyFLUplhKsxZaFuL3pirmYqbfBSEBJ-44p3CxVTD6rQXbiGVhFZSlrEC3VlD3Ah7FnGCHnv9BF7o1lbvPUZzxIHaooy47ShltrYF854ZgsclBuBzEVw6OPftpf0d-P94Bow74KEpY_68knp-mneQnLvOSHg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3096927869</pqid></control><display><type>article</type><title>Explore the genetic exposure to alopecia areata</title><source>MEDLINE</source><source>Wiley Online Library Open Access</source><source>Wiley Online Library Journals Frontfile Complete</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Peng, Shaoyi ; Yang, Yang ; Man, Yilong ; Long, Dianfei ; Wang, Lei ; Li, Kaiyuan ; Liu, Peng</creator><creatorcontrib>Peng, Shaoyi ; Yang, Yang ; Man, Yilong ; Long, Dianfei ; Wang, Lei ; Li, Kaiyuan ; Liu, Peng</creatorcontrib><description>Background
Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation.
Methods
This study employed Mendelian randomization (MR), utilizing data from genome‐wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR‐Egger regression intercept test, MR‐PRESSO global test, and leave‐one‐out analysis, to assess the robustness of the results.
Results
MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75–0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values < 0.05).
Conclusion
This study provides genetic evidence of the relationships between trace elements, serum metabolites, and alopecia areata, underscoring the potential value of targeted therapeutic strategies and preventive measures. Future research should expand to diverse populations and further explore the specific roles of these biomarkers in the disease mechanism.</description><identifier>ISSN: 0909-752X</identifier><identifier>ISSN: 1600-0846</identifier><identifier>EISSN: 1600-0846</identifier><identifier>DOI: 10.1111/srt.13874</identifier><identifier>PMID: 39086160</identifier><language>eng</language><publisher>England: John Wiley & Sons, Inc</publisher><subject>Alopecia ; alopecia areata ; Alopecia Areata - blood ; Alopecia Areata - genetics ; Baldness ; Biomarkers ; Confidence intervals ; Genetic Predisposition to Disease - genetics ; Genome-Wide Association Study ; Humans ; Inflammatory diseases ; inflammatory factors ; mendelian randomization ; Mendelian Randomization Analysis ; Metabolites ; Original ; Polymorphism, Single Nucleotide ; Sensitivity analysis ; serum metabolites ; Statistical analysis ; Trace elements ; Trace Elements - blood</subject><ispartof>Skin research and technology, 2024-08, Vol.30 (8), p.e13874-n/a</ispartof><rights>2024 The Author(s). published by John Wiley & Sons Ltd.</rights><rights>2024 The Author(s). Skin Research and Technology published by John Wiley & Sons Ltd.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3344-2eb9ea8ca79c81376b37bb620cae5cfd1d350686090b330e9d8cf26cbdce350b3</cites><orcidid>0009-0004-3094-4851</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11291861/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11291861/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,1411,11541,27901,27902,45550,45551,46027,46451,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39086160$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Peng, Shaoyi</creatorcontrib><creatorcontrib>Yang, Yang</creatorcontrib><creatorcontrib>Man, Yilong</creatorcontrib><creatorcontrib>Long, Dianfei</creatorcontrib><creatorcontrib>Wang, Lei</creatorcontrib><creatorcontrib>Li, Kaiyuan</creatorcontrib><creatorcontrib>Liu, Peng</creatorcontrib><title>Explore the genetic exposure to alopecia areata</title><title>Skin research and technology</title><addtitle>Skin Res Technol</addtitle><description>Background
Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation.
Methods
This study employed Mendelian randomization (MR), utilizing data from genome‐wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR‐Egger regression intercept test, MR‐PRESSO global test, and leave‐one‐out analysis, to assess the robustness of the results.
Results
MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75–0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values < 0.05).
Conclusion
This study provides genetic evidence of the relationships between trace elements, serum metabolites, and alopecia areata, underscoring the potential value of targeted therapeutic strategies and preventive measures. Future research should expand to diverse populations and further explore the specific roles of these biomarkers in the disease mechanism.</description><subject>Alopecia</subject><subject>alopecia areata</subject><subject>Alopecia Areata - blood</subject><subject>Alopecia Areata - genetics</subject><subject>Baldness</subject><subject>Biomarkers</subject><subject>Confidence intervals</subject><subject>Genetic Predisposition to Disease - genetics</subject><subject>Genome-Wide Association Study</subject><subject>Humans</subject><subject>Inflammatory diseases</subject><subject>inflammatory factors</subject><subject>mendelian randomization</subject><subject>Mendelian Randomization Analysis</subject><subject>Metabolites</subject><subject>Original</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Sensitivity analysis</subject><subject>serum metabolites</subject><subject>Statistical analysis</subject><subject>Trace elements</subject><subject>Trace Elements - blood</subject><issn>0909-752X</issn><issn>1600-0846</issn><issn>1600-0846</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNp1kU9Lw0AQxRdRbK0e_AIS8KKHtLvZZJM9iZT6BwRBK3hbNptJm5Jm426i7bd3a2pRwbkMzPx4vJmH0CnBQ-JqZE0zJDSJwz3UJwxjHych20d9zDH34yh47aEjaxcY44gTeoh6lOOEObKPRpNVXWoDXjMHbwYVNIXyYFVr226G2pOlrkEV0pMGZCOP0UEuSwsn2z5ALzeT6fjOf3i8vR9fP_iK0jD0A0g5yETJmKuE0JilNE5TFmAlIVJ5RjIaYZYw5zClFAPPEpUHTKWZArdJ6QBddbp1my7BTavGyFLUplhKsxZaFuL3pirmYqbfBSEBJ-44p3CxVTD6rQXbiGVhFZSlrEC3VlD3Ah7FnGCHnv9BF7o1lbvPUZzxIHaooy47ShltrYF854ZgsclBuBzEVw6OPftpf0d-P94Bow74KEpY_68knp-mneQnLvOSHg</recordid><startdate>202408</startdate><enddate>202408</enddate><creator>Peng, Shaoyi</creator><creator>Yang, Yang</creator><creator>Man, Yilong</creator><creator>Long, Dianfei</creator><creator>Wang, Lei</creator><creator>Li, Kaiyuan</creator><creator>Liu, Peng</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0009-0004-3094-4851</orcidid></search><sort><creationdate>202408</creationdate><title>Explore the genetic exposure to alopecia areata</title><author>Peng, Shaoyi ; Yang, Yang ; Man, Yilong ; Long, Dianfei ; Wang, Lei ; Li, Kaiyuan ; Liu, Peng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3344-2eb9ea8ca79c81376b37bb620cae5cfd1d350686090b330e9d8cf26cbdce350b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Alopecia</topic><topic>alopecia areata</topic><topic>Alopecia Areata - blood</topic><topic>Alopecia Areata - genetics</topic><topic>Baldness</topic><topic>Biomarkers</topic><topic>Confidence intervals</topic><topic>Genetic Predisposition to Disease - genetics</topic><topic>Genome-Wide Association Study</topic><topic>Humans</topic><topic>Inflammatory diseases</topic><topic>inflammatory factors</topic><topic>mendelian randomization</topic><topic>Mendelian Randomization Analysis</topic><topic>Metabolites</topic><topic>Original</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Sensitivity analysis</topic><topic>serum metabolites</topic><topic>Statistical analysis</topic><topic>Trace elements</topic><topic>Trace Elements - blood</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peng, Shaoyi</creatorcontrib><creatorcontrib>Yang, Yang</creatorcontrib><creatorcontrib>Man, Yilong</creatorcontrib><creatorcontrib>Long, Dianfei</creatorcontrib><creatorcontrib>Wang, Lei</creatorcontrib><creatorcontrib>Li, Kaiyuan</creatorcontrib><creatorcontrib>Liu, Peng</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Skin research and technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peng, Shaoyi</au><au>Yang, Yang</au><au>Man, Yilong</au><au>Long, Dianfei</au><au>Wang, Lei</au><au>Li, Kaiyuan</au><au>Liu, Peng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Explore the genetic exposure to alopecia areata</atitle><jtitle>Skin research and technology</jtitle><addtitle>Skin Res Technol</addtitle><date>2024-08</date><risdate>2024</risdate><volume>30</volume><issue>8</issue><spage>e13874</spage><epage>n/a</epage><pages>e13874-n/a</pages><issn>0909-752X</issn><issn>1600-0846</issn><eissn>1600-0846</eissn><abstract>Background
Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation.
Methods
This study employed Mendelian randomization (MR), utilizing data from genome‐wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR‐Egger regression intercept test, MR‐PRESSO global test, and leave‐one‐out analysis, to assess the robustness of the results.
Results
MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75–0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values < 0.05).
Conclusion
This study provides genetic evidence of the relationships between trace elements, serum metabolites, and alopecia areata, underscoring the potential value of targeted therapeutic strategies and preventive measures. Future research should expand to diverse populations and further explore the specific roles of these biomarkers in the disease mechanism.</abstract><cop>England</cop><pub>John Wiley & Sons, Inc</pub><pmid>39086160</pmid><doi>10.1111/srt.13874</doi><tpages>8</tpages><orcidid>https://orcid.org/0009-0004-3094-4851</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Alopecia alopecia areata Alopecia Areata - blood Alopecia Areata - genetics Baldness Biomarkers Confidence intervals Genetic Predisposition to Disease - genetics Genome-Wide Association Study Humans Inflammatory diseases inflammatory factors mendelian randomization Mendelian Randomization Analysis Metabolites Original Polymorphism, Single Nucleotide Sensitivity analysis serum metabolites Statistical analysis Trace elements Trace Elements - blood |
| title | Explore the genetic exposure to alopecia areata |
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