Personalized Targeted Prevention and Therapy Relied on Detection of Global and Local Single Nucleotide Polymorphisms (original) (raw)
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Single Nucleotide Polymorphisms (SNPs): History, Biotechnological Outlook and Practical Applications
Current Pharmacogenomics, 2005
The recent introduction of molecular biology methods to pharmacology, to assess how DNA sequence variations can influence the response of an individual to a drug, has opened new dimensions in the evidence based analysis of goals, risks and benefits of drug therapy. The development of diagnostic test systems to identify patients at increased risk of adverse drug reactions, the application of genomic technologies to drug development, and the clarification of the mechanisms of drug action on cells represent actual challenges for both clinicians and researchers. In this review, we emphasize on the investigative tools of molecular biology-based pharmacology with particular reference to the development of single nucleotide polymorphisms (SNPs) and new developing trends of this technology.
SNPs: At the origins of the databases of an innovative biotechnology tool
Frontiers in bioscience (Scholar edition), 2010
The discovery that DNA sequence variations can influence the response of an individual to a drug or can predict the outcome of a disease has added a new dimension to evidence-based medicine. It is clear that the goals, risks, and benefits of drug therapy can be better assessed if the underlying genome of the patient is known. The relevance of identifying patients at increased risk of adverse drug reactions, the application of genomic technologies to drug development and the clarification of the mechanisms of drug action on cells will be important targets in the therapeutic approach to medicine in the 21st century. In this review, we summarize the development of single nucleotide polymorphisms (SNPs) and give computational biological data for SNPs databases.
Candidate Genes and Single Nucleotide Polymorphisms (SNPs) in the Study of Human Disease
Disease Markers, 2001
The genomic revolution has generated an extraordinary resource, the catalog of variation within the human genome, for investigating biological, evolutionary and medical questions. Together with new, more efficient platforms for high-throughput genotyping, it is possible to begin to dissect genetic contributions to complex trait diseases, specifically examining common variants, such as the single nucleotide polymorphism (SNP). At the same time, these tools will make it possible to identify determinants of disease with the expectation of eventually, tailoring therapies based upon specific profiles. However, a number of methodological, practical and ethical issues must be addressed before the analysis of genetic variation becomes a standard of clinical medicine. The currents of variation in human biology are reviewed here, with a specific emphasis on future challenges and directions.
Biological communications, 2022
The review highlights various methods for deciphering the nucleotide sequence (sequencing) of nucleic acids and their importance for the implementation of the three main principles of personalized medicine: prevention, predictability and personalization. The review, along with its own practical examples, considers three generations of sequencing technologies: 1) sequencing of cloned or amplified DNA fragments according to Sanger and its analogues; 2) massive parallel sequencing of DNA libraries with short reads (NGS); and 3) sequencing of single molecules of DNA and RNA with long reads. The methods of whole genome, whole exome, targeted, RNA sequencing and sequencing based on chromatin immunoprecipitation are also discussed. The advantages and limitations of the above methods for diagnosing monogenic and oncological diseases, as well as for identifying risk factors and predicting the course of socially significant multifactorial diseases are discussed. Using examples from clinical practice, algorithms for the application and selection of sequencing technologies are demonstrated. As a result of the use of sequencing technologies, it has now become possible to determine the molecular mechanism of the development of monogenic, orphan and multifactorial diseases, the knowledge of which is necessary for personalized patient therapy. In science, these technologies paved the way for international genome projects-the Human Genome Project, the HapMap, 1000 Genomes Project, the Personalized Genome Project, etc.
Pharmacogenomics: Advent of personalized medicine
Mini Review, 2013
Pharmacogenomics is the technology that analyses how genetic makeup affects an individual's response to drugs. Pharmacogenomics helps to predict respond to a medication and negative side effects. It aims to develop effective, safe drug and optimize drug therapy with respect to the patients' genotype which leads to maximum efficacy and minimal adverse effects. Pharmacogenomics combines knowledge of genes, proteins and single nucleotide polymorphisms (SNPs) to speed the discovery of drug response markers. It has implications in disease like heart disease, cancer, asthma, HIV, depression and many other common diseases.
Personalized Genome, Current Status, and the Future of Pharmacogenomics
Omics for Personalized Medicine, 2013
Adverse drug reactions (ADRs) are one of the most dreadful medical conditions that affect a considerable number of individuals when they are taking single or multiple prescription drugs. Often these adverse reactions can occur with specialized drugs that are used to treat more serious disorders. Seldom ADRs can also occur due to intake of even simpler drugs such as penicillin and aspirin. In spite of volumes of data on ADRs, at present we still go through "one size fi ts all" model in dealing with prescription drugs. This scenario could change due to the emergence of new ways to overcome or minimize ADRs. Pharmacogenomics is one such ways to overcome many horrors of side effects caused by drugs, including ADRs. Pharmacogenomics is the combination of pharmacy and the patient's genetic composition which interact in an intricate manner to produce positive as well as negative drug reactions. When positive, it is for the betterment of patients, and when negative it leads to ADRs which oftentimes is fatal. Pharmacogenomics is an emerging fi eld of science which is still in its infancy. Technologies that were developed along with the Human Genome Project (HGP), such as faster DNA sequencing protocols and effi cient data handling softwares would help in the rapid advancement of pharmacogenomics in the near future. In addition, the reduced cost to obtain complete sequence of individual genome would provide data on single nucleotide polymorphisms (SNPs) and haplotype map (HapMap). These data would provide pattern of individual genetic variations which could be useful in managing diseases and treating patients effectively. In this chapter we will look at the current status and the future of pharmacogenomics which will aid in the development of personalised care. We will also discuss some of the obstacles that would have to be dealt with in achieving such target.
Genome-wide SNP discovery in associating with human diseases phenotypes
Single Nucleotide Polymorphisms or SNPs are a most abundant, stable and simple base pair changes that occur in the genome. It is an important variation that can be used to describe many unsolved problems in modern medicine such as individual variation to disease response, differences in response to treatment, allergies to drug treatment, etc. Monogenic Mendalian diseases are very rear and most of the time the disease has complex multigenetic involvement. With the advancement of sequencing technologies SNP discovery is becoming fast, accurate and less expensive. As a result the availability of SNP data has become more abundant and is used to create SNPmap and SNPprofile. This SNP map and SNP profile helps to locate the genes that involve some complex diseases like diabetes, vascular diseases, and mental disorders and to describe individual variation in response to treatment as well as finding a drug target in pharmacogenomics. With such developments in Bioinformatics, the dream of "individualized treatment" is becoming a reality.
Journal of translational medicine, 2003
Detection of unknown single nucleotide polymorphism (SNP) relies on large scale sequencing expeditions of genomic fragments or complex high-throughput chip technology. We describe a simplified strategy for fluorimetric detection of known and unknown SNP by proportional hybridization to oligonucleotide arrays based on optimization of the established principle of signal loss or gain that requires a drastically reduced number of matched or mismatched probes. The array consists of two sets of 18-mer oligonucleotide probes. One set includes overlapping oligos with 4-nucleotide tiling representing an arbitrarily selected "consensus" sequence (consensus-oligos), the other includes oligos specific for known SNP within the same genomic region (variant-oligos). Fluorescence-labeled DNA amplified from a homozygous source identical to the consensus represents the reference target and is co-hybridized with a differentially-labeled test sample. Lack of hybridization of the test sample t...
Clinical SNP Detection by the SmartAmp Method
For advancing personalized medicine, it is important to incorporate pharmacogenomics data into routine clinical practice. The SmartAmp method enables us to detect genetic polymorphisms or mutations in target genes within 30–40 min without DNA isolation and PCR amplifi cation. The SmartAmp method has been developed based on the concept that DNA amplifi cation per se is the signal for the presence of a specifi c target sequence. Differing from the widely used PCR, the SmartAmp reaction is an isothermal DNA amplifi cation, where the initial step of copying a target sequence from the template DNA is critically important. For clinical applications, we have created SmartAmp primers and clinical device that detect genetic polymorphisms of human genes involved in drug-induced toxicity or disease risk. This chapter addresses both the basic molecular mechanism underlying the SmartAmp method and its practical applications to detect clinically important single nucleotide polymorphisms (SNPs).