{"title":"Detection of hemophilia A genetic variants using third-generation long-read sequencing","authors":"","doi":"10.1016/j.cca.2024.119884","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Hemophilia A (HA) is an X-linked recessive genetic disorder caused by pathogenic variations of the factor VIII −encoding gene, <em>F8</em> gene. Due to the large size and diverse types of variations in the <em>F8</em> gene, causative mutations in <em>F8</em> cannot be simultaneously detected in one step by traditional molecular analysis, and genetic molecular diagnosis and prenatal screening of HA still face significant difficulties and challenges in clinical practice. Therefore, we aimed to develop and validate an efficient, accurate, and time-saving method for the genetic detection of HA.</p></div><div><h3>Methods</h3><p>A comprehensive analysis of hemophilia A (CAHEA) method based on long-range PCR and long-read sequencing (LRS) was used to detect <em>F8</em> gene mutations in 14 clinical HA samples. The LRS results were compared with those of the conventional methods to evaluate the accuracy and sensitivity of the proposed approach.</p></div><div><h3>Results</h3><p>The CAHEA method successfully identified 14 <em>F8</em> variants in all probands, including 3 small insertion deletions, 4 single nucleotide variants, and 7 intron 22 inversions in a “one-step” manner, of which 2 small deletions have not been reported previously. Moreover, this method provided an opportunity to analyze the mechanism of rearrangement and the pathogenicity of <em>F8</em> variants. The LRS results were validated and found to be in 100% agreement with those obtained using the conventional method.</p></div><div><h3>Conclusion</h3><p>Our proposed LRS-based <em>F8</em> gene detection method is an accurate and reproducible genetic screening and diagnostic method with significant clinical value. It provides efficient, comprehensive, and accurate genetic screening and diagnostic services for individuals at high risk of HA as well as for premarital and prenatal populations.</p></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0009898124021375","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Hemophilia A (HA) is an X-linked recessive genetic disorder caused by pathogenic variations of the factor VIII −encoding gene, F8 gene. Due to the large size and diverse types of variations in the F8 gene, causative mutations in F8 cannot be simultaneously detected in one step by traditional molecular analysis, and genetic molecular diagnosis and prenatal screening of HA still face significant difficulties and challenges in clinical practice. Therefore, we aimed to develop and validate an efficient, accurate, and time-saving method for the genetic detection of HA.
Methods
A comprehensive analysis of hemophilia A (CAHEA) method based on long-range PCR and long-read sequencing (LRS) was used to detect F8 gene mutations in 14 clinical HA samples. The LRS results were compared with those of the conventional methods to evaluate the accuracy and sensitivity of the proposed approach.
Results
The CAHEA method successfully identified 14 F8 variants in all probands, including 3 small insertion deletions, 4 single nucleotide variants, and 7 intron 22 inversions in a “one-step” manner, of which 2 small deletions have not been reported previously. Moreover, this method provided an opportunity to analyze the mechanism of rearrangement and the pathogenicity of F8 variants. The LRS results were validated and found to be in 100% agreement with those obtained using the conventional method.
Conclusion
Our proposed LRS-based F8 gene detection method is an accurate and reproducible genetic screening and diagnostic method with significant clinical value. It provides efficient, comprehensive, and accurate genetic screening and diagnostic services for individuals at high risk of HA as well as for premarital and prenatal populations.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.