Precision diagnostics is a branch of precision medicine that involves managing a patient's healthcare model and diagnosing specific diseases based on omics data analytics. The U.S. announced federal funding for precision medicine research efforts in 2015 with the Precision Medicine Initiative. A year later, the Human Personal Omics Profiling study was established to develop integrative multi-omics approaches for use in precision diagnostics. Individuals receive an early disease diagnosis based on their variability in DNA, environment, and lifestyle. Precision diagnostics utilize recent technological advancements in the acquisition of data from genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiome. It helps gain a comprehensive understanding of an individual's personal molecular profile by monitoring collateral molecular layers. Furthermore, modern computing improves the analysis of the omics data generated. Precision diagnostics utilizes advancements in artificial intelligence, specifically convolutional neural networks and data analysis, to predict the relationship between genotype and phenotype, potentially enhancing the sensitivity and specificity of precision diagnoses. The advancement of next-generation sequencing (NGS) has improved cancer diagnostics. NGS provides a more comprehensive view of the genome than other single-gene assays. NGS-based molecular diagnostics give genomic information about tumor-related variants and structural changes that cause cancer. This lets doctors make very accurate diagnoses and use targeted therapies that work with them. NGS samples can be collected using a buccal swab, peripheral blood, or tissue-specific biopsy, and DNA is used to screen for single nucleotide variants, gene insertions and deletions and copy number variants, while RNA is used to measure gene expression.
Precision diagnostics techniques
DNA sequencing DNA sequencing is an essential component of modern scientific translational research, and the use of DNA sequencing in the clinical environment was introduced first in clinical oncology. Whole genome sequencing is used extensively for cancer patients. It is used to help give further genetic information about the patient's background as well as their eligibility for clinical trials that may be beneficial to them. The advantage of using WGS is that it reduces overall cost and time for the clinic to pass the diagnostics stage and apply treatments for the patient. Genetic sequencing can also be performed later on when a patient's disease progresses. Furthermore, using germline data, clinical may evaluate cancer predisposition and pharmacogenomics information for earlier cancer identification and treatment. Despite some challenges, such as accessibility to lower-income patients, healthcare systems around the world have started to invest into holistic genomic sequencing and data infrastructure. The importance of fast access to the high-dimensional output of genomic data is growing.
RNA sequencing Single-cell RNA sequencing and dual host-pathogen RNA sequencing are some of the commercially available RNA sequencing technologies. RNA-Seq allows clinicians to trace cancers when other diagnostic results are ambiguous. RNA sequencing allows further cell trajectory analysis that may give additional insight into cancer subtypes and patient backgrounds. As a more advanced version of whole genome sequencing, RNA sequencing gives additional information when creating an individual patient's treatment plan. The importance of RNA sequencing in the diagnostics of malignant disorders, such as leukoplakia, is increasing. Transcriptome analysis may also reveal disease progression in pro-malignant conditions. Such analysis allows for an individualized prognosis for each patient. The utilities for the sequencing of blood, bone marrow, or other bodily systems are becoming increasingly obvious. Using the database, clinicians may become more informed of the patient's situation.
Proteomics Proteomics is the study of proteins. Proteins that are translated from messenger RNA go through post-transcriptional modifications that include phosphorylation, ubiquitination, methylation, acetylation, glycosylation, etc. Previously, immunoassay methods were used to study proteins, but mass spectrometry is now mainly used as a proteomic analyzing tool. In mass spectrometry analysis, proteins/peptides are fragmented. Then, peptides are ionized through either electrospray ionization or matrix-assisted laser desorption/ionization (MALDI). In addition to this, a mass analyzer generates information-rich ion mass spectra from fragmented peptides. Four types of mass analyzers include ion trap, time-of-flight, quadrupole, and Fourier transform ion cyclotron. Lastly, using computational bioinformatics tools and algorithms, collected proteomics data can be further analyzed and used for protein profiling.
Microbiome In recent years, the interest in microbiome research has been rising and has become one of the critical components in precision medicine. Microbiome research refers to the studying of microorganisms' interaction within and outside of the host. Common microorganisms include different types of fungi, bacteria, and viruses, and the community of microorganisms is known as the microbiome. These microorganisms exist in most of our body parts, contributing to our health. According to research, this microbiome is crucial in regulating our physiology by altering our metabolism, immune system, and more. Hence, the changes in the microbial community can provide insights into the health condition of the specific host and patient. In precision medicine, patients' gut microbiome is often profiled in order to determine which treatment offers the most therapeutic value to them. Evidence shows that the microbiome is essential as it may increase the effectiveness of specific cancer treatments.
Diagnostics in specific disease conditions
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