Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: Network is unreachable
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
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
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Background: Pre-implantation genetic testing for monogenic disorders (PGT-M) is an effective approach to reducing the incidence of birth defects by preventing the transmission of inherited diseases to offspring. However, there are still controversies regarding the detection methods and transplantation of embryos. This paper aims to evaluate the effectiveness of different detection technologies applied to PGT-M through a retrospective analysis of clinical detection data.
Methods: The carrier status of pathogenic mutations and chromosomal copy number variants (CNVs) in 892 embryos was characterized using next-generation sequencing (NGS), single-nucleotide polymorphism (SNP) array, and PCR-based detection technologies. Clinical data from PGT-M cases were retrospectively analyzed to assess the effectiveness of these detection methods in identifying genetic abnormalities in embryos.
Results: A total of 829 embryos were analyzed, with 63 being unsuccessful. Our study revealed that the success rate of detecting deletional mutations using Gap-PCR 84.9%, which is lower than that of SNP array (98.7%) and NGS (92.5%). However, no significant difference was observed when detecting point mutations using any of the methods. These findings suggest that, when detecting deletional mutations, SNP array and NGS are more suitable choices compared to Gap-PCR. While SNP array may have a lower resolution and success rate (80.5%) in analyzing CNVs compared to NGS (95.5%), it may still be useful for revealing certain abnormal types.
Conclusion: In conclusion, this study found that SNP analysis is advantageous for identifying polygenic and deletional mutations, whereas NGS is more cost-efficient for detecting common monogenic diseases. Additionally, SNP-based haplotyping and PCR-based direct detection of mutations can be used together to enhance the accuracy and success rates of PGT-M. Our findings offer valuable insights for PGT technicians in choosing suitable detection methods for patients.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10767435 | PMC |
http://dx.doi.org/10.1002/mgg3.2293 | DOI Listing |