Pharmacogenomics (a portmanteau of pharmacology and genomics) is the technology that analyses how genetic makeup affects an individual's response to drugs. It deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity. By doing so, pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to the patients' genotype, to ensure maximum efficacy with minimal adverse effects. Such approaches promise the advent of "personalized medicine"; in which drugs and drug combinations are optimized for each individual's unique genetic makeup. In order to provide pharmacogenomic based recommendations for a given drug, two possible types of input can be used: genotyping or exome or whole genome sequencing. Sequencing provides many more data points, including detection of mutations that prematurely terminate the synthesized protein (early stop codon).
There are several known genes which are largely responsible for variances in drug metabolism and response. The most common are the cytochrome P450 (CYP) genes, which encode enzymes that influence the metabolism of more than 80 percent of current prescription drugs. Codeine, clopidogrel, tamoxifen, and warfarin are examples of medications that follow this metabolic pathway. Patient genotypes are usually categorized into predicted phenotypes. For example, if a person receives one *1 allele each from mother and father to code for the CYP2D6 gene, then that person is considered to have an extensive metabolizer (EM) phenotype. An extensive metabolizer is considered normal. Other CYP metabolism phenotypes include: intermediate, ultra-rapid, and poor. In theory, each phenotype is based upon the allelic variation within the individual genotype. However, several genetic events can influence a same phenotypic trait, and establishing genotype-to-phenotype relationships can thus be far from consensual with many enzymatic patterns. For instance, the influence of the CYP2D6*1/*4 allelic variant on the clinical outcome in patients treated with Tamoxifen remains debated today. In oncology, genes coding for DPD, UGT1A1, TPMT, CDA involved in the pharmacokinetics of 5-FU/capecitabine, irinotecan, 6-mercaptopurine and gemcitabine/cytarabine, respectively, have all been described as being highly polymorphic. A strong body of evidence suggests that patients affected by these genetic polymorphisms will experience severe/lethal toxicities upon drug intake, and that pre-therapeutic screening does help to reduce the risk of treatment-related toxicities through adaptive dosing strategies.
Identification of the genetic basis for polymorphic expression of a gene is done through intronic or exomic SNPs which abolishes the need for different mechanisms for explaining the variability in drug metabolism. The SNPs based variations in membrane receptors lead to multidrug resistance (MDR) and the drug–drug interactions. Even drug induced toxicity and many adverse effects can be explained by genome-wide association studies (GWAS).
In cancer treatment, pharmacogenomics tests are used to identify which patients are most likely to respond to certain cancer drugs. In behavioral health, pharmacogenomic tests provide tools for physicians and care givers to better manage medication selection and side effect amelioration. Pharmacogenomics is also known as companion diagnostics, meaning tests being bundled with drugs. Examples include KRAS test with cetuximab and EGFR test with gefitinib. Beside efficacy, germline pharmacogenetics can help to identify patients likely to undergo severe toxicities when given cytotoxics showing impaired detoxification in relation with genetic polymorphism, such as canonical 5-FU.
Some alleles that vary in frequency between specific populations have been shown to be associated with differential responses to specific drugs. The beta blocker Atenolol is an anti-hypertensive medication that is shown to more significantly lower the blood pressure of Caucasian patients than African American patients in the United States. This observation suggests that Caucasian and African American populations have different alleles governing oleic acid biochemistry, which react differentially with Atenolol. Similarly, hypersensitivity to the antiretroviral drug abacavir is strongly associated with a single-nucleotide polymorphism that varies in frequency between populations.
The FDA approval of the drug BiDil with a label specifying African-Americans with congestive heart failure, produced a storm of controversy over race-based medicine and fears of genetic stereotyping, even though the label for BiDil did not specify any genetic variants but was based on racial self-identification.
- Population groups in biomedicine
Affects one in three adults
Affecting about 35 percent of all adults in the United States according to the CDC, metabolic syndrome contributes to weight gain, by causing a state of internal starvation called metabolic starvation. This in turn leads to increases hunger, sugar cravings and increased portions leading to overeating and weight gain.
Cause and effect misunderstood
Since we traditionally thought that the portion control (which in turn was attributed wrongly to poor will power)is the cause of weight gain, rather than the effect of this metabolic starvation, all our traditional ideas about cause and effect of obesity were not only wrong but lead to the “blame the victim” attitude when it comes to obesity.
Secret of weight gain revealed
Secret of weight gain, and metabolic syndrome revealed - it has been recently proven that metabolic syndrome, and the weight gain itself are caused by a process called insulin resistance. Check your metabolic syndrome risk using the free Metabolic syndrome meter. Watch this amazing Ted Med video that reveals the secret of weight loss - Stop blaming the victim for obesity