{"id":5419,"date":"2020-08-26T09:44:29","date_gmt":"2020-08-26T09:44:29","guid":{"rendered":"https:\/\/clinlabint.3wstaging.nl\/clinical-application-of-ngs-ensuring-quality\/"},"modified":"2021-01-08T11:37:10","modified_gmt":"2021-01-08T11:37:10","slug":"clinical-application-of-ngs-ensuring-quality","status":"publish","type":"post","link":"https:\/\/clinlabint.com\/clinical-application-of-ngs-ensuring-quality\/","title":{"rendered":"Clinical application of NGS \u2013 ensuring quality"},"content":{"rendered":"
Advances in Next Generation Sequencing (NGS) are bringing much higher throughput and rapidly reducing costs, whilst facilitating new mechanisms for disease prediction. Consequently, the clinical applications of NGS technologies are continuing to develop, with the potential to change the face of genetic medicine [1].<\/p>\n by Hannah Murfet (BSc, PCQI), Product Quality Manager, Horizon Discovery<\/strong><\/p>\n Applications of NGS in a clinical context are varied, and may include interrogation of known disease-related genes as part of targeted gene panels, exome sequencing, or genome sequencing of both coding and non-coding regions. However, as NGS moves further into the clinic, care must be taken to ensure high levels of quality assurance, rigorous validation, recording of data, quality control, and reporting are maintained. [1] [2] Quality Assurance<\/strong> Validation<\/strong> Data<\/strong> Robustness<\/strong><\/em><\/p>\n Precision<\/strong><\/em><\/p>\n Repeatability and Reproducibility<\/strong><\/em><\/p>\n Analytical Sensitivity and Specificity<\/strong><\/em><\/p>\n A minimum data set is expected, to establish key performance characteristics, including: base calling; read alignment; variant calling; and variant annotation. Reports<\/strong> References<\/strong> Advances in Next Generation Sequencing (NGS) are bringing much higher throughput and rapidly reducing costs, whilst facilitating new mechanisms for disease prediction. Consequently, the clinical applications of NGS technologies are continuing to develop, with the potential to change the face of genetic medicine [1]. by Hannah Murfet (BSc, PCQI), Product Quality Manager, Horizon Discovery Applications […]<\/p>\n","protected":false},"author":2,"featured_media":9911,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[52],"tags":[],"_links":{"self":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/5419"}],"collection":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/comments?post=5419"}],"version-history":[{"count":0,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/5419\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/media\/9911"}],"wp:attachment":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/media?parent=5419"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/categories?post=5419"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/tags?post=5419"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Guidelines specific to NGS are beginning to emerge and to be adopted by clinical laboratories working with these technologies, in addition to those mandated by clinical accreditation and certification programmes. In this article we give an overview of the specific guidance set out by the American College of Medical Genetics and Genomics in its September 2013 report \u2018ACMG clinical laboratory standards for next-generation sequencing\u2019, and the New York State Department of Health\u2019s January 2014 document \u2018Next Generation Sequencing (NGS) guidelines for somatic genetic variant detection\u2019.<\/p>\n
Quality assurance (QA) in the clinical context comprises maintenance of a desired level of quality for laboratory services. Typically, quality management systems take a three tier hierarchy. At the highest level the policies define the organisation\u2019s strategy and focus. Underneath this sit the procedures, which define and document instructions for performing business\/quality management or technical activities. Underpinning both of these tiers are accurate records.
In the case of New York State Department of Health guidelines, there is clear focus on the requirement for SOPs, which can be broken down into two levels. The first level states the required flow of information, demonstrating the sequence of events, and associated responsibilities or authorities. The first level procedures are best kept at a relatively high level, and may reference more specific and detailed level two processes.
Testing sequences may be incorporated into one or more level one processes, depending on the complexity of the clinical laboratory\u2019s operations. An overview of the typical testing sequence is shown in the figure below.
Level two processes are best documented as clear \u2018how to\u2019 guides, detailing all responsibilities, materials and procedures necessary to complete the activity. For laboratory-focused activities, validation study inputs and outputs can establish clear and consistent protocols, supporting training and laboratory operation.
Accurate record keeping should include which instruments were used in each test, as well as documentation of all reagent lot numbers. Any deviations from standard procedures should be recorded, including any corrective measures [1]. Templates may be generated to ensure consistency in output records for both testing and reporting.
In addition to documented processes, implementation of predetermined checkpoints or key performance indicators should be included to permit the monitoring of QA over time. Once established, these may act as a trigger for assay drift, operator variability, or equipment issues.
In the US, compliance to the HIPAA Act (Health Insurance Portability and Accountability Act) must be implemented to ensure traceability and protection of patient data, and many authorities mandate record retention periods, including CLIA who dictate that records and test reports must be stored for at least two years [1].
Clinical laboratories may look to further certification to ensure tight QA, such as the implementation of ISO 15189, especially in countries where no formal accreditation schemes are in place. [3]<\/p>\n
Validation involves the in-depth assessment of protocols, tests, materials and platforms, providing confidence that critical requirements are being met. Test development and platform optimization should include factors such as determination of sample pooling parameters, and use of synthetic variants to create a strong data set, to compare tools and optimize the workflow. Validation of each entire test should be undertaken, using set conditions for sensitivity, specificity, robustness and reproducibility. It should be noted that the first test developed may naturally carry a higher validation burden than subsequent tests developed for the same platform. Platform validation and quality management are also vital. [1,2]
Specific validation requirements for NGS as set out by the New York State Department of Health are listed below. These guidelines may be used as a basic checklist for coverage, or to supplement more general accreditation or certification requirements, e.g. those required by CLIA or ISO 15189. [1]<\/p>\n\n
NGS has the potential to create huge amounts of data, meaning that accurate and efficient systems for data storage and collection are more essential than ever. Data protocols are generally established through the validation stages, then monitored at predetermined checkpoints with key performance indicators to ensure consistency and accuracy of service provision.
The list below gives an overview of NGS specific data requirements from the New York State Department of Health. [1]
\n
Accuracy<\/strong><\/em><\/p>\n\n
\n
\n
\n
\n
Quality Control<\/strong>
In contrast to quality assurance where the infrastructure for quality is established to maintain the right service, quality control addresses testing and sampling to confirm outputs against requirements. Quality control takes place across all aspects of a process from reagents used, to software and in-assay controls.
Quality control of reagent lots is best implemented at the point of goods inspection. A clear label should be placed on the reagent under inspection, and testing performed to validate\/confirm analytical sensitivity. Quality control of software updates can be handled through a version control and impact assessment process. All re-validation must be clearly documented and demonstrate consistency in analytical sensitivity.
Sample identity confirmation is essential, especially if samples are pooled. Proficiency testing protocols must be established to allow for execution as required by clinical accreditation bodies (such as CLIA). Quality control stops may be added to laboratory process before the sequencing run, to the run itself and at the end before data analysis.
Use of control materials \/reagents at all stages of the sequencing procedure supports quality control. No Template Controls (NTC) should be used at all amplification steps; a negative Control should be used upon initial validation, and periodically thereafter; and a Positive \/ Sensitivity Control should be used in each sequencing run. [1]
Several different QC protocols may need to be followed, and quality control measures applied can vary depending on chosen methods and instrumentation, but they should always include procedures to identify sample preparation failures and failed sequencing runs. Documentation for QC protocols is best detailed in the relevant SOP.<\/p>\n
Specific requirements around the generation, approval, issue and re-issue of reports are included as part of accreditation programmes, such as CLIA, and standards certifications, such as ISO 15189. The most essential reporting requirements related to NGS are as follows [1,2]:<\/p>\n\n
Conclusions<\/strong>
While complete understanding of the clinical implications of some variants is still to be fully understood, there are clear prospects emerging for NGS to support further development and adoption of companion diagnostics. As the overall picture for NGS evolves, sell-defined guidelines are being developed for everything from quality assurance to reporting. It is expected that guidance and certification will continue to develop as NGS becomes an ever more common technology within the clinical laboratory.<\/p>\n
1. American College of Medical Genetics and Genomics. (2013, September). ACMG clinical laboratory standards for next-generation sequencing.
2. New York State Department of Health. (2014, January). \u201cNext Generation\u201d Sequencing (NGS) guidelines for somatic genetic variant detection.
3. Horizon Discovery. (n.d.). ISO 15189: A Standard of Yin and Yang.<\/p>\nwww.horizondx.com<\/link>\n","protected":false},"excerpt":{"rendered":"