Applications of Digital PCR in Clinical Diagnostics
2023-06
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Applications of Digital PCR in Clinical Diagnostics
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2023-06
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Genetic testing has become increasingly relevant to advanced precision medicine for carrier screening, genetic susceptibility, and molecular diagnosis of human disease. Real-time quantitative PCR (qPCR) is considered the gold-standard technique for detection and quantification of nucleic acids. Yet, significant qPCR shortcomings are described including poor reproducibility, insufficient limit of detection, low tolerance to inhibitory substances, and reliance on reference material for calibration, which hinder standardization of qPCR assays across laboratories. Digital PCR (dPCR) has emerged as a novel molecular technology that promises unsurpassed sensitivity and precision while overcoming most qPCR limitations. Sample partitioning and digital counting in dPCR enable rapid and accurate absolute quantification of molecular markers without the need for standard curves. In this work, new analytical dPCR protocols were successfully developed, validated, and implemented for three important conditions: (1) quantification of ultra-low-levels of congenital cytomegalovirus in dried blood spots, urine and saliva of newborns, (2) genotyping and quantification of mitochondrial variants associated with aminoglycoside-induced hearing loss in individuals with cystic fibrosis, (3) multiplex quantification of SMN1 and SMN2 genes for newborn screening, carrier screening, and diagnostic testing of spinal muscular atrophy. Altogether, these studies demonstrate that dPCR provides enhanced sensitivity and reproducibility in the detection and quantification of nucleic acid with reduced background and minimal effect of PCR inhibitors. The low-cost high throughput workflow makes dPCR amenable for numerous applications. The advent of dPCR in clinical diagnostics can revolutionize genetic testing by enabling early detection and disease prevention, both critical for timely treatment and improved health outcomes in patient care.
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University of Minnesota Ph.D. dissertation. June 2023. Major: Biomedical Informatics and Computational Biology. Advisors: Devin Oglesbee, Yuk Sham. 1 computer file (PDF); viii, 107 pages.
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Vidal-Folch, Noemi. (2023). Applications of Digital PCR in Clinical Diagnostics. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/258680.
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