One of the challenges of the 21st century for medical researchers and pharmaceutical companies is to be able to predict the body's response to a given drug and to understand the factors that relate to the inter-individual variability of this response. Response to drugs varies extremely from one subject to another, both pharmacologically and toxicologically. One of the limitations of drug prescription is the difficulty of predicting the variability of this response. The number of death and global annual cost related to hospitalizations and work stoppages regarding drug effects are increasing. These findings raise the issue of the question of interindividual variations in therapeutic response as a major public health problem. The Human Genome Project has made it possible to discover several single nucleotide polymorphisms (SNPs) which have a frequency = 1% within the same species. These variations are frequent, almost one base pair in a thousand, and are mostly biallelic and codominant. Thus, SNPs located at the level of genes involved in drug metabolism can strongly modify drug bioavailability and impact the therapeutic response, hence the notion of pharmacogenetics/pharmacogenomics.
In the post-genomic era where genetic information determines the health and disease of the individual, molecular genetics - thanks to recombinant DNA techniques - is fast becoming first choice in current medical practices. It operates in the field of complex diseases, in particular for the determination of subjects at risk (preventive genetics) or in the therapeutic management of patients according to their genetic profile (pharmacogenetics or personalized medicine).
The goal of this research topic is to improve our understanding regarding the impact of individual genetic variations on treatment response. In particular, we want to understand the influence of genetic heritage on the response to treatment of various diseases including infectious, cancerous, cardiovascular, endocrine, respiratory, digestive, rheumatological, neurological, eye, hematological, psychiatric and autoimmune diseases.
We welcome contributions from researchers whose work closely examines the impact of genetic background on interindividual variability in treatment by exploring different diseases, using candidate gene or whole genome approaches. To address this topic, we welcome a range of article types: original research paper, review articles, short communication on genetic biomarkers in treatment response to drugs. Please also note the following:
• If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities as well as additional clinical information and assessment of drug response/effects should be included.
• If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for the selection of the specific data studied should be provided.
• Studies related to natural compounds, herbal extracts, or traditional medicine products, will not be included in this Research Topic.
One of the challenges of the 21st century for medical researchers and pharmaceutical companies is to be able to predict the body's response to a given drug and to understand the factors that relate to the inter-individual variability of this response. Response to drugs varies extremely from one subject to another, both pharmacologically and toxicologically. One of the limitations of drug prescription is the difficulty of predicting the variability of this response. The number of death and global annual cost related to hospitalizations and work stoppages regarding drug effects are increasing. These findings raise the issue of the question of interindividual variations in therapeutic response as a major public health problem. The Human Genome Project has made it possible to discover several single nucleotide polymorphisms (SNPs) which have a frequency = 1% within the same species. These variations are frequent, almost one base pair in a thousand, and are mostly biallelic and codominant. Thus, SNPs located at the level of genes involved in drug metabolism can strongly modify drug bioavailability and impact the therapeutic response, hence the notion of pharmacogenetics/pharmacogenomics.
In the post-genomic era where genetic information determines the health and disease of the individual, molecular genetics - thanks to recombinant DNA techniques - is fast becoming first choice in current medical practices. It operates in the field of complex diseases, in particular for the determination of subjects at risk (preventive genetics) or in the therapeutic management of patients according to their genetic profile (pharmacogenetics or personalized medicine).
The goal of this research topic is to improve our understanding regarding the impact of individual genetic variations on treatment response. In particular, we want to understand the influence of genetic heritage on the response to treatment of various diseases including infectious, cancerous, cardiovascular, endocrine, respiratory, digestive, rheumatological, neurological, eye, hematological, psychiatric and autoimmune diseases.
We welcome contributions from researchers whose work closely examines the impact of genetic background on interindividual variability in treatment by exploring different diseases, using candidate gene or whole genome approaches. To address this topic, we welcome a range of article types: original research paper, review articles, short communication on genetic biomarkers in treatment response to drugs. Please also note the following:
• If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities as well as additional clinical information and assessment of drug response/effects should be included.
• If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for the selection of the specific data studied should be provided.
• Studies related to natural compounds, herbal extracts, or traditional medicine products, will not be included in this Research Topic.
