Shaoyi Peng, Yang Yang, Yilong Man, Dianfei Long, Lei Wang, Kaiyuan Li, Peng Liu
{"title":"探索遗传因素对斑秃的影响。","authors":"Shaoyi Peng, Yang Yang, Yilong Man, Dianfei Long, Lei Wang, Kaiyuan Li, Peng Liu","doi":"10.1111/srt.13874","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":21746,"journal":{"name":"Skin Research and Technology","volume":"30 8","pages":"e13874"},"PeriodicalIF":2.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11291861/pdf/","citationCount":"0","resultStr":"{\"title\":\"Explore the genetic exposure to alopecia areata.\",\"authors\":\"Shaoyi Peng, Yang Yang, Yilong Man, Dianfei Long, Lei Wang, Kaiyuan Li, Peng Liu\",\"doi\":\"10.1111/srt.13874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":21746,\"journal\":{\"name\":\"Skin Research and Technology\",\"volume\":\"30 8\",\"pages\":\"e13874\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11291861/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Skin Research and Technology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/srt.13874\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DERMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Skin Research and Technology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/srt.13874","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DERMATOLOGY","Score":null,"Total":0}
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.
期刊介绍:
Skin Research and Technology is a clinically-oriented journal on biophysical methods and imaging techniques and how they are used in dermatology, cosmetology and plastic surgery for noninvasive quantification of skin structure and functions. Papers are invited on the development and validation of methods and their application in the characterization of diseased, abnormal and normal skin.
Topics include blood flow, colorimetry, thermography, evaporimetry, epidermal humidity, desquamation, profilometry, skin mechanics, epiluminiscence microscopy, high-frequency ultrasonography, confocal microscopy, digital imaging, image analysis and computerized evaluation and magnetic resonance. Noninvasive biochemical methods (such as lipids, keratin and tissue water) and the instrumental evaluation of cytological and histological samples are also covered.
The journal has a wide scope and aims to link scientists, clinical researchers and technicians through original articles, communications, editorials and commentaries, letters, reviews, announcements and news. Contributions should be clear, experimentally sound and novel.