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Updated: Aug 14, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
From single cell gene-based diagnostics to diagnostic genomics: current applications and future perspectives
1Division Head of Molecular Pathology, Department of Pathology, University of Maryland Medical Center, Baltimore, MD 21201-1192, USA. rzhao@som.umaryland.edu
Abstract:
Molecular diagnostics is a branch of clinical diagnostics that uses primarily DNA or RNA as a biomarker for clinical testing. It combines various gene-based amplification technologies with highly sophisticated detection methods for the clinical diagnosis of a vast variety of diseases including infectious diseases, cancer, and inherited diseases. The principal application of gene-based amplification technology is to identify pathogen or gene-specific nucleic acid sequences that are used as surrogate markers for the identification of either infectious pathogens or alteration of disease-related genes. There are generally three classes of gene-based amplification technologies: target-based, e.g., PCR; probe-based, e.g., LCR; and signal-based, e.g., bDNA. Real-time detection of PCR allows us to quantify amplified amplicons with a broad dynamic range and it offers a unique way to detect genetic mutations. Other technologies such as immuno-PCR and bio-barcode assay (BCA) combine different amplification tactics offering extreme detection sensitivity ranging from femtogram (10(-15)) to zeptogram (10(-21)). Even though quantum dots technology is in its infant stage, its potential to further increase diagnostic sensitivity and specificity is likely beyond our current imagination. Future diagnostic technologies include the use of genomic and proteomic approaches especially in pure cell types or even in the single-cell level, which open up endless new possibilities for gene-based diagnostics at entirely different levels. In this article, principles of various current gene-based amplification and detection technologies along with their clinical applications are discussed. New technologies that could potentially be used in future gene-based diagnosis are introduced.
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