Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Craniofacial microsomia (CFM, OMIM%164 210) is one of the most common congenital facial abnormalities worldwide, but it's genetic risk factors and environmental threats are poorly investigated, as well as their interaction, making the diagnosis and prenatal screening of CFM impossible. We perform a comprehensive association study on the largest CFM cohort of 6074 samples. We identify 15 significant (P < 5 × 10-8) associated genomic loci (including eight previously reported) and decipher 107 candidates based on multi-omics data. Gene Ontology term enrichment found that these candidates are mainly enriched in neural crest cell (NCC) development and hypoxic environment. Single-cell RNA-seq data of mouse embryo demonstrate that nine of them show dramatic expression change during early cranial NCC development whose dysplasia is involved in pathogeny of CFM. Furthermore, we construct a well-performed CFM risk-predicting model based on polygenic risk score (PRS) method and estimate seven environmental risk factors that interacting with PRS. Single-nucleotide polymorphism-based PRS is significantly associated with CFM [P = 7.22 × 10-58, odds ratio = 3.15, 95% confidence interval (CI) 2.74-3.63], and the top fifth percentile has a 6.8-fold CFM risk comparing with the 10th percentile. Father's smoking increases CFM risk as evidenced by interaction parameter of -0.324 (95% CI -0.578 to -0.070, P = 0.011) with PRS. In conclusion, the newly identified risk loci will significantly improve our understandings of genetics contribution to CFM. The risk prediction model is promising for CFM prediction, and father's smoking is a key environmental risk factor for CFM through interacting with genetic factors.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1093/hmg/ddab055 | DOI Listing |
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