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 Table of Contents  
Year : 2022  |  Volume : 6  |  Issue : 1  |  Page : 14-20

A review of literature on the pharmacogenomics of single-nucleotide polymorphisms

1 Medical Students, RAK College of Medical Sciences, RAK Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates
2 Department of and Biochemistry, RAK College of Medical Sciences, RAK Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates

Date of Submission25-Sep-2021
Date of Acceptance12-Nov-2021
Date of Web Publication11-Mar-2022

Correspondence Address:
Iffath Ahmed
RAK College of Medical Sciences, RAK Medical and Health Sciences University, P O Box. 11172, Ras Al Khaimah
United Arab Emirates
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/bbrj.bbrj_245_21

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Pharmacogenomics is the study of how our genetic structure determines the response to a therapeutic intervention. It is a rapidly growing field that aims to elaborate the genetic basis for differences in drug response between different individuals and to use such genetic information to predict the safety, toxicity, and/or efficacy of drugs in individual patients or groups of patients. Although drug–drug interactions and environmental factors significantly contribute to interindividual variability in drug response, genetic factors (e.g., inherited variability of drug targets, drug-metabolizing enzymes, and/or drug transporters) also appear to have a major impact on drug response and disposition. When a gene variant is associated with a particular drug response in a patient, there is the potential for making clinical decisions based on genetics by adjusting the dosage or choosing a different drug. Single-nucleotide polymorphisms (SNPs), also called SNPs, are the most common type of genetic variation among people. They are basically a substitution of a single nucleotide that occurs at a specific position in the genome. They occur normally throughout a person's DNA. They occur almost once in every 1000 nucleotides on average, which means there are roughly 4–5 million SNPs in a person's genome. Most SNPs have no effect on health or development. Some of them, however, have proven to be very important in the study of human health, especially in the field of pharmacogenomics. Researchers have found SNPs that may help predict an individual's response to certain drugs, susceptibility to environmental factors such as toxins, and risk of developing particular diseases. Scientists assess gene variants affecting an individual's drug response the same way they assess gene variants associated with diseases: by identifying genetic loci associated with known drug responses, and then testing individuals whose response is unknown. SNPs account for the most common genetic differences from person to person and pharmacogenomics explores how such changes in genetic makeup effect drug responses, resistance, etc., With our literature review, we aim to study some of the effects of these SNPs on drug responses in patients. The purpose of the study was to understand and implicate the effects of SNPs in modern medicine and how it can be applied to personalize health care for every patient. A systematic literature search was carried in search of studies pertaining to personalized medicine and implications of SNPs. A thorough search through PubMed, Google Scholar, and ProQuest revealed 61 relevant studies. All study types were considered eligible. Over the past 10 years, tremendous progress has been made in cataloging human sequence variations since this high-density map can offer the required tools to develop genetically based diagnostic and therapeutic tests. When additional functional polymorphisms are known, it may be attainable to develop helpful genetic markers also as personalized medicines. In the future, the main aim is to use SNPs not only to find certain aspects to be used in the future (individualized drug therapy, development of genome-based diets, etc.) but to also unveil the details of genome evolution. A number of challenges exist today in realizing the value of a high-density map of anonymous SNPs for pharmacogenomics. Concerns about the high price of genotyping are being addressed; however, it may be several years before the price of genotyping large populations is acceptable. In addition, availability of large patient populations will be crucial for discovering and validating SNPs.

Keywords: Advances in medicine, biotechnology, personalized medicine, pharmacogenomics, single-nucleotide polymorphisms

How to cite this article:
Ahmed I, Siddiqui HI, Qureshi GS, Bernhardt GV. A review of literature on the pharmacogenomics of single-nucleotide polymorphisms. Biomed Biotechnol Res J 2022;6:14-20

How to cite this URL:
Ahmed I, Siddiqui HI, Qureshi GS, Bernhardt GV. A review of literature on the pharmacogenomics of single-nucleotide polymorphisms. Biomed Biotechnol Res J [serial online] 2022 [cited 2023 Jan 28];6:14-20. Available from: https://www.bmbtrj.org/text.asp?2022/6/1/14/339374

  Introduction Top

Every individual carries two copies of each gene which may not be the same throughout the population. One of the reasons for human diversity is these scattered single-nucleotide polymorphisms (SNPs) that tend to occur in humans every 300–2000 base pairs along the genome. SNPs are variations in the human genome and they are responsible for a person's response to medications and against diseases.

SNPs work either by altering the pharmacokinetics of the drugs or changing the cellular response to those drugs. They are being studied to personalize medicine according to a person's genotype and to reduce their toxicity.[1]

Individual differences in reaction to a drug (particularly adverse reactions) due to SNPs are one of the major causes of discontinuation of that particular drug. Many other factors, namely age, sex, and weight, do play a role as well, but genetic susceptibility is of the most importance.[2],[3],[4]

Pharmacogenomics helped researchers in optimizing drug therapy which is specifically tailored and better suited for genetically susceptible individuals.[5]

Pharmacogenomics is the study of how a person's genetic makeup affects their response to drugs and therapeutic interventions in general. This could potentially individualize treatments saving time and money in the long run by reducing uncertainty in drug regimes and minimizing drug-induced toxicity.

They can be used to study diseases with complex inheritance pathways and higher social burden such as cardiovascular diseases, inflammatory disorders, diabetes, and cancers. Moreover, SNPs are abundant, have low mutation rates, and unlike single tandem repeats, do not usually act as surrogate markers which makes it possible to test a direct association between a phenotype and functional variant. This makes SNPs highly preferred for drawing the high-density genetic marker maps required for unraveling complex genetic traits.[6]


The aim of this review is to define SNPs and their implications in medicine.

  Methods Top

Articles on the pharmacogenomics of SNPs were searched and identified through research journals and web-based sources.

A thorough search through PubMed, Google Scholar, and ProQuest revealed 61 relevant studies. All study types were considered eligible.

Search criteria

A systematic literature search was carried in search of studies pertaining to personalized medicine and implications of SNPs.

Single-nucleotide polymorphisms

When sequencing the human genome, scientists noticed mismatched base pairs every 1000 base pairs, for example, guanine paired with thymine instead of cytosine. This kind of mismatching, if prevalent in 1% of the population, was termed as SNPs[7] SNPs that altered the final amino acid sequence of protein were termed as nonsynonymous[8] and they are the ones that cause polymorphisms resulting in differences in genes coding for various drug receptors, enzymes, cell signaling pathways, etc. These are hence important determinants of clinical response.[9]

SNPs play a huge role in personalized medicine[10] They are the most frequently seen variants in the human genome[11] A person's response to a drug can be done by sequencing their genome by Biotech companies via next-generation sequencing (NGS).[12],[13]

Single-nucleotide polymorphisms in evolution

Genetic evolution, along with other factors, depends on “a balance of natural selection and environmentally driven mutations.” Natural selection preserves amino acids which are vital for protein function and eliminate deleterious mutations. The selection pressure against these harmful mutations generally depends on the functions of proteins. It has been noted that genes that encode transcriptional regulatory proteins are generally under the strongest selective pressure.[14]

SNPs may be used to study evolution and variation between species as they are widely present and are passed down the generations. Generally, these variants are not fixed in a genome. If they are, it can be assumed or inferred that they can be either advantageous, be neutral or cause pathologies after deletions.[14]

A comparative genomic study of pathologic SNPs can be performed to find out the relationship between the pathology and evolution.[14]

It was noted that regions that were conserved during evolution were more likely to contain SNPs that could lead to disease as compared to regions that were not. Moreover, SNPs that were not present in coding regions were under significantly less selective pressure.[14]

Pharmacogenetics and pharmacogenomics

When it comes to diseases such as cardiac arrhythmia, renal cell carcinoma, liver cancer, and pulmonary hypertension, certain drugs tend to work better in certain patients and be fatal to others. The answer to why this happens lies in pharmacogenetics and pharmacogenomics. SNPs are the culprit when it comes to inter-individual differences in drug response. Another aspect is enzymes. Patients who inhabit active drug-metabolizing enzymes may necessitate higher doses of drugs, whereas patients who do not might show signs of toxicity. It is important to note that drug response is also highly dependent on other factors such as ethnicity, environmental factors, and inheritance pattern.

Understanding the extent of SNP influence on drug response may open doors to individualized treatment as opposed to the trial-and-error approach that is widely used today.[14]

The use of single-nucleotide polymorphism maps in pharmacogenomics

SNP maps can be used in two ways in pharmacogenomics: candidate gene approach and linkage-disequilibrium mapping.[6]

Candidate gene approach

  • This approach works by learning from experience. Through case–control or cohort studies, genes relevant to each disease are identified. The probability of an individual getting a disease can then be calculated using statistics[6]
  • Moreover, it can be used to identify the effect of certain genes on drug response. It has been found that variations in thiopurine methyltransferase have been linked to adverse reactions.

Linkage-disequilibrium mapping

  • This method helps identify regions without any previous knowledge that harbor a genome that may contain susceptible genes. Then, using positioning cloning, the gene and the SNPs within that gene can be found.


It is an unbiased technique.

Disadvantages and limitations

  1. It has only been successful in families with several individuals with monogenic diseases and not in unrelated individuals
  2. It has not been able to identify genetic predictors of diseases
  3. Thousands of markers are necessary, this increases the chance of false positives.
  4. Since every person in the study has to undergo genotyping, the process is extremely expensive. If DNA pooling is performed to decrease the cost, there will be technical challenges since subtype and haplotype analysis will not be possible.[6]

Implications of single-nucleotide polymorphisms in medicine and drug response

In microRNA-binding sites of oncogenes

  • Neoplasms are caused by abnormalities on two fronts – loss of function of tumor suppressor genes and gain of function of oncogenes. Classically, cancer occurs by the transformation of proto-oncogenes into oncogenes through mutations. Recently, it was discovered that cancer may also occur due to loss of microRNA-binding sites due to either the translocation of 3'untranslated region (3'UTR) or by the use of alternative polyadenylation signals that may shorten 3'UTR[15]
  • UTRs are the regulatory factors that play crucial roles in gene expression. More than 60% of protein-coding mRNA transcripts have target sequences in their 3'UTR to which miRNAs bind, leading to translational repression. Genetic aberrations and exogenous episomal integrations that adjust those miRNA target sites are of clinical significance, as they will lead to severe problems[15]
  • It was speculated that 3'UTR SNPs in miRNA target destinations of proto-oncogenes could annul cis-regulation coming about in oncogenic change, disease inclination, and tweak of medication reaction. The strategy used in this examination depends on the conventional miRNA–mRNA restricting site corresponding and concordant cross expectation by three distinct calculations. The SNP included objective locales of miRNAs that were separated dependent on their miRSVR and all-out setting scores.[15]

Effects of methylene tetrahydrofolate reductase single-nucleotide polymorphisms on MTX Efficacy and toxicity in rheumatoid arthritis

  • MTX is a disease-modifying antirheumatic drugs (DMARD) that is used for the treatment of rheumatoid arthritis (RA). It has been proven to reduce the disease progression and bone erosions. It works by inhibiting enzymes of the folate pathway[16]
  • It has been found to work with a good clinical response only in 50% of the RA patients put on MTX therapy[16]
  • Though MTX has its side effects, it has been strongly suggested to begin therapy early to reduce the disease progression[16]
  • Best trial is a 2-year randomized clinical trial that compared the clinical effect of 4 different drugs in early R.[16]
  • This was tested on 508 patients divided into four groups of different treatment regimens as:

    1. Sequential therapy starting with MTX
    2. Step up combination therapy starting with MTX
    3. Initial combination therapy with MTX, sulfasalazine, and high-dose prednisolone
    4. Initial therapy with Infliximab and MTX.[16]

  • Out of the 508 patients, groups 1 and 2 were analyzed for drug response since their regimen began with MTX as the first-line drug. These patients were started with a dose of 7.5 mg/week of MTX which was later increased to 15 mg/week after 4 weeks with a combination of 1 mg/day folic acid. This dose was increased to 25 mg/week in case of an insufficient clinical response after 3 months.[16]

The efficacy of the drug was studied and analyzed at intervals of 3 and 6 months by comparing the genotype distribution and their clinical response. Specifically, the Disease Activity Score (DAS44) was studied in 44 joints. Patients who responded to MTX were classified as DAS44 ≤2.4 and nonresponders as DAS >2.4. This confounder along with the RF value proved to be statistically significant in the study.[16]

  • Five SNPs in three genes encoding for methylene tetrahydrofolate reductase (MTHFR), dihydrofolate reductase (DHFR), and reduced folate carrier (RFC) were identified and genotyping was performed using MassARRAY assay[16]
  • At the end of 3 months, this study found that 22% of the patients were good responders and at the end of 6 months, this percentage increased to 47%. About 43% of these patients were taking 15 mg of MTX/week and 57% were taking 25 mg of MTX/week[16]
  • MTHFR 1298AA was associated with a good response DAS44 <2.4. It was found that MTHFR 1298AC + CC was associated with a higher number of adverse drug effects in comparison with the MTHFR1298AA genotype[16]
  • This study shows that this gene (MTHFR 1298AA) is associated with a DAS44 improvement within the first 6 months of MTX treatment[16]
  • Patients with the MHTFR 1298AA phenotype show a better clinical improvement at 6 months compared to the 1298CC carriers[16]
  • The BeSt trial did not find any association with the MTHFR 677T gene and the ADE of MTX which was consistent with the findings of van Ede et al[16],[61]
  • According to recent studies initiated by Urano et al., two SNPs (677C >T and 1298A >C) in the MTHFR gene may be linked to altered phenotypes and adverse drug effects in rheumatoid arthritis patients. Although previously 677T has been linked to MTX toxicity and hepatotoxicity, the report by Urano et al. is the first to demonstrate and report that the 677T allele is linked to greater toxicity whereas 1298C allele has been associated with better efficacy (without specifying the degree of the side effects caused due to the toxicity)[17],[62],[63]
  • After the intake of methotrexate, folate levels may drop lower than normal due to the fact that methotrexate may cause the body to get rid of more folate as waste than usual. This effect causes folate deficiency
  • It can usually be treated by taking folate supplements[17]
  • It is important to explore the link between MTHFR SNPs and MTX toxicity and whether they are related to higher folate depletion by methotrexate in patients with inherited MTHFR deficiency, as doctors could then prescribe folate supplementation. According to previously conducted clinical trials, when folate supplementation is provided, lower MTX hepatotoxicity is documented without the efficacy being reduced[17]
  • For example, in the case of cancers or bone marrow transplants, an association between MTHFR 677 SNP and methotrexate toxicity had been noticed only in low doses of MTX. This may be due to the fact that high-dose MTX is only given with folic acid. Therefore, this supports the fact that MTX given with folate supplementation may decrease drug-induced toxicity in patients with inherited folate metabolism deficiency[17]


  • Drugs used in asthma include beta-adrenergic agonists, corticosteroids, and leukotriene inhibitors.[18]

  1. Beta-adrenergic agonist: People with SNPs in the gene coding for adrenoceptor beta 2 show alterations in response to beta-adrenergic agonist drugs. Two main variations of this gene exist: one at amino acid 16 (Gly16Arg) and the other at 27 (Gln27Glu).[19] It was noted that people with Gly16Arg showed a better response toward the drug but suffered more side effects.[20],[21],[22]
  2. Leukotriene inhibitor: ALOX5 gene encodes the enzyme 5-lipoxygenase which is responsible for making leukotrienes. A polymorphism in the promoter region of this gene leads to downregulation of the enzyme and hence decreased leukotriene metabolism leads to decreased responsiveness to leukotriene inhibitors[23]
  3. Corticosteroids: Increased corticosteroid response was shown in people with rs2429411 SNP polymorphism

Alzheimer's disease

Alterations in choline acetyltransferase expression due to mutations in the APOE gene leads to altered response to Tacrine (a centrally active cholinesterase inhibitor) therapy.[24]


Diuretics, angiotensin-converting enzyme (ACE) inhibitors, calcium channel blockers, beta-blockers, and angiotensin-II receptor blockers are drugs used in the treatment of hypertension.

  1. Diuretics

    • SNP in alpha-adducin (ADD1) gene in some patients taking diuretics showed reduced cardiovascular consequences and stroke, whereas some patients showed no association whatsoever[25]
    • SNP in alpha-adducin (ADD1) gene in some patients taking diuretics showed reduced cardiovascular consequences and stroke, whereas some patients showed no association whatsoever[25]
    • SNP in the GNB3825TT (rs5443) gene showed a greater reduction in blood pressure with diuretic therapy compared to individuals with SNP in the GNB3825CC gene[26]
    • SNP in the renin gene enhances the effect of thiazide diuretics[27]

  2. Beta-blockers: Polymorphisms in the ADRB1 gene showed significantly reduced blood pressure with beta-blocker therapy.[28],[29]
  3. ACE inhibitors

    • Renin–angiotensin–aldosterone system gene polymorphism has an effect on responsiveness of ACE. Mutation in the ACE gene itself is linked to effective lowering of blood pressure with ACE-I[30]
    • The Met235Thr, C11537A (rs7079), rs2638362 (C/T), and rs2640543 (G/A) alleles are found to have a connection with blood pressure response to ACE inhibitors
    • Bradykinin B1 receptor (BDKRB1) gene, SNP (rs12050217), and the ABO gene polymorphisms (rs495828 and rs8176746) are associated SNPs too.

Rheumatoid arthritis

It was observed that not all individuals undergoing therapy for RA respond equally to treatment for which SNPs are held accountable.[31]


  • SNPs in the drug transporter (RFC-1 and multidrug resistance gene-1) and metabolizing enzymes (MTHFR, thymidylate synthetase [TYMS], DHFR, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase [ATIC]) are known to effect efficacy and toxicity[32],[33],[34]
  • RFC 80A/A genotype showed a better response to the drug compared to 80G/G genotype[35]
  • 3435T/T genotype responds better than 3435C/C and 3435 C/T genotype and hence have less risk of RA.[36]
  • A fixed effects model confirmed an associated between C677T polymorphism and methotrexate toxicity.[37],[63]


  • SNPs in the gene coding N-acetyl transferase 2 (NAT2) affects the rate of acetylation of sulfasalazine which in turn alters toxicity and efficacy of the drug[40]
  • In the future, the severity of RA could even be based on the type of NAT2 mutation the patient has
  • High (homozygous NAT2 * 4)
  • Moderate (heterozygous NAT2 * 4)
  • Low (homozygous variant alleles).[38]


  • The drug is discontinued in patients with mutations in the thiopurine methyltransferase (TPMT) gene
  • Half the required dose is given to patients with low TPMT activity, whereas it is contraindicated in patients with no TPMT activity.[41]



  • The enzyme uridine diphosphate glucuronosyltransferase 1A1 (UTG1A1) metabolizes the toxic metabolite of irinotecan and SNPs in the promoter region of UTG1A1 gene effect the efficacy and safety of the drug[42],[43],[44],[45]
  • High risk of neutropenia is associated with the UGT1A1 * 28 allele which decreases UTG1A1 levels[44]
  • Less efficient response is also seen with the UGT1A1 * 28 allele[46]
  • Recent studies showed that UGT1A1 * 28 genotype produces similar levels of toxicity at low doses as other patients but produce severe hematological toxicity at intermediate doses[47]
  • UGT1A1, UGT1A7, and UGT1A9 polymorphisms should also be assessed to predict irinotecan-induced toxicity.


  • Patients with low dihydropyrimidine dehydrogenase (DPD) enzyme leads to accumulation of 5-FU in the body leading to toxicity viz. mucositis, neutropenia, neurological symptoms, and death.[48],[49],[50],[51]
  • G to A point mutation in the GT splicing recognition sequence of the DPYD gene results in skipping of the entire exon preceding the mutation and inactivation of DPYD gene which results in a decrease in Dihydropyrimidine dehydrogenase (DPD) expression large enough to cause 5-FU toxicity. Therefore, a genotyping test for the G to A splicing point mutation may prove to be useful in predicting toxicity in cancer patients upon administration of 5-FU[52]
  • 5-FU toxicity can also be due to polymorphisms in the TYMS and MTHFR genes
  • 5-FU targets TS and overexpression of TS causes resistance to 5-FU and other TYMS inhibitors.[53],[54],[55]
  • A functional genetic polymorphism in the TS gene may alter the enzyme's function which could in turn affect cancer susceptibility and the toxicity of drugs such as 5-FU[39]
  • TSER*3 (three tandem mutations) show high levels of TS mRNA expression compared to TSER*2 (two tandem mutations).[56]


6-Mercaptopurine is metabolized by an array of enzymes and SNPs in the genes coding for these enzymes leads to toxicity in patients with acute lymphoblastic leukemia.[57],[58]


  • Tamoxifen is metabolized by CYP450 and genetic polymorphisms in it effects the drugs activity and toxicity
  • CYP2D6 10, CYP2D6, and CYP2D6 41 are common variations that reduces the activity of tamoxifen
  • Patients having wild-type alleles have better rates of survival than patients with CYP2D6 4 allele.[59]

  Conclusion Top

There is little question that clinicians, geneticists, patients, and therefore the public can have the benefit of the identification of genes underlying inheritable diseases and adverse drug reactions. Over the past 10 years, tremendous progress has been made in cataloging human sequence variations since this high-density map can offer the required tools to develop genetically based diagnostic and therapeutic tests.

When additional functional polymorphisms are known, it may be attainable to develop helpful genetic markers also as personalized medicines.

In the future, the main aim is to use SNPs not only to find certain aspects to be used in the future (individualized drug therapy, development of genome-based diets, etc.,) but also to unveil the details of genome evolution.[14]

SNPs are predicted to be used to identify disease causing genes and understand drug response, but it can also be noted that SNPs can be used to understand evolution.

There is an evident relationship between selective pressure and diseases. It was shown that residues that overcome strong selective pressures are more likely to cause disease.[14]

Evolution and disease-causing nucleotide substitutions are closely related as nucleotide substitutions may remain neutral or become deleterious depending on whether or not they are advantageous for the organism.[14]

Pharmacogenomics requires extensive correlation of genetic and clinical data. It mostly depends on data gathered from clinical trials done on limited/selected ethnic groups although the drug is sold worldwide and is used by several different ethnic groups. Hence, a lot of pharmacogenomic studies are limited to these clinical trial population.[60]

NGS technology is expensive and its interpretation is also a limiting factor.[61]

Although the functionality of MTHFR 677C >T and 1298A > C has not fully been explored, it has been shown that the effects of the mutant alleles lead to higher thermolability and a decrease in enzyme activity.

It has been shown that disease duration and previous treatment influence MTX outcome, and van Ede et al.'s cohort included patients with persistent RA who had previously taken other DMARDs.

A number of challenges exist today in realizing the value of a high-density map of anonymous SNPs for pharmacogenomics. Concerns about the high price of genotyping are being addressed; however, it may be several years before the price of genotyping large populations is acceptable. In addition, availability of large patient populations will be crucial for discovering and validating SNPs.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Sauna ZE, Kimchi-Sarfaty C, Ambudkar SV, Gottesman MM. Silent polymorphisms speak: How they affect pharmacogenomics and the treatment of cancer. Cancer Res 2007;67:9609-12.  Back to cited text no. 1
Evans WE, McLeod HL. Pharmacogenomics-drug disposition, drug targets, and side effects. N Engl J Med 2003;348:538-49.  Back to cited text no. 2
Evans WE, Relling MV. Moving towards individualized medicine with pharmacogenomics. Nature 2004;429:464-8.  Back to cited text no. 3
Weinshilboum R. Inheritance and drug response. N Engl J Med 2003;348:529-37.  Back to cited text no. 4
Cappelen AW, Norheim OF, Tungodden B. Genomics and equal opportunity ethics. J Med Ethics 2008;34:361-4.  Back to cited text no. 5
Alwi ZB. The use of SNPs in pharmacogenomics studies. Malays J Med Sci 2005;12:4-12.  Back to cited text no. 6
Kirk BW, Feinsod M, Favis R, Kliman RM, Barany F. Single nucleotide polymorphism seeking long term association with complex disease. Nucleic Acids Res 2002;30:3295-311.  Back to cited text no. 7
Hunt R, Sauna ZE, Ambudkar SV, Gottesman MM, Kimchi-Sarfaty C. Silent (Synonymous) SNPs: Should We Care about Them? Single Nucleotide Polymorphisms; 2009. p. 23-39.  Back to cited text no. 8
Nebert DW, Wikvall K, Miller WL. Human cytochromes P450 in health and disease. Philos Trans R Soc Lond B Biol Sci 2013;368:20120431.  Back to cited text no. 9
Wang J, Pang GS, Chong SS, Lee CG. SNP web resources and their potential applications in personalized medicine. Curr Drug Metab 2012;13:978-90.  Back to cited text no. 10
Kwok PY, Chen X. Detection of single nucleotide polymorphisms. Curr Issues Mol Biol 2003;5:43-60.  Back to cited text no. 11
Useche FJ, Gao G, Harafey M, Rafalski A. High-throughput identification, database storage and analysis of SNPs in EST sequences. Genome Inform 2001;12:194-203.  Back to cited text no. 12
van Oeveren J, Janssen A. Mining SNPs from DNA sequence data; computational approaches to SNP discovery and analysis. In: Single Nucleotide Polymorphisms. Totowa, NJ.: Humana Press; 2009. p. 73-91.  Back to cited text no. 13
Shastry BS. SNPs in disease gene mapping, medicinal drug development and evolution. J Hum Genet 2007;52:871-80.  Back to cited text no. 14
Manikandan M, Munirajan AK. Single nucleotide polymorphisms in microRNA binding sites of oncogenes: Implications in cancer and pharmacogenomics. OMICS 2014;18:142-54.  Back to cited text no. 15
Wessels JA, de Vries-Bouwstra JK, Heijmans BT, Slagboom PE, Goekoop-Ruiterman YP, Allaart CF, et al. Efficacy and toxicity of methotrexate in early rheumatoid arthritis are associated with single-nucleotide polymorphisms in genes coding for folate pathway enzymes. Arthritis Rheum 2006;54:1087-95.  Back to cited text no. 16
Evans WE. Differing effects of methylenetetrahydrofolate reductase single nucleotide polymorphisms on methotrexate efficacy and toxicity in rheumatoid arthritis. Pharmacogenetics 2002;12:181-2.  Back to cited text no. 17
Park HW, Tantisira KG, Weiss ST. Pharmacogenomics in asthma therapy: Where are we and where do we go? Annu Rev Pharmacol Toxicol 2015;55:129-47.  Back to cited text no. 18
Liggett SB. Polymorphisms of adrenergic receptors: Variations on a theme. Assay Drug Dev Technol 2003;1:317-26.  Back to cited text no. 19
Kotani Y, Nishimura Y, Maeda H, Yokoyama M. Beta2-adrenergic receptor polymorphisms affect airway responsiveness to salbutamol in asthmatics. J Asthma 1999;36:583-90.  Back to cited text no. 20
Lima JJ, Mohamed MH, Self TH, Eberle LV, Johnson JA. Importance of beta (2) adrenergic receptor genotype, gender and race on albuterol-evoked bronchodilation in asthmatics. Pulm Pharmacol Ther 2000;13:127-34.  Back to cited text no. 21
Martinez FD, Graves PE, Baldini M, Solomon S, Erickson R. Association between genetic polymorphisms of the beta2-adrenoceptor and response to albuterol in children with and without a history of wheezing. J Clin Invest 1997;100:3184-8.  Back to cited text no. 22
Kalayci O, Birben E, Sackesen C, Keskin O, Tahan F, Wechsler ME, et al. ALOX5 promoter genotype, asthma severity and LTC production by eosinophils. Allergy 2006;61:97-103.  Back to cited text no. 23
Poirier J, Delisle MC, Quirion R, Aubert I, Farlow M, Lahiri D, et al. Apolipoprotein E4 allele as a predictor of cholinergic deficits and treatment outcome in Alzheimer disease. Proc Natl Acad Sci U S A 1995;92:12260-4.  Back to cited text no. 24
Turner ST, Schwartz GL, Chapman AB, Boerwinkle E. WNK1 kinase polymorphism and blood pressure response to a thiazide diuretic. Hypertension 2005;46:758-65.  Back to cited text no. 25
Yu H, Lin S, Jin L, Yu Y, Zhong J, Zhang Y, et al. Adenine/cytosine (1166) polymorphism of the angiotensin II type 1 receptor gene and the antihypertensive response to angiotensin-converting enzyme inhibitors. J Hypertens 2009;27:2278-82.  Back to cited text no. 26
Huang CC, Chung CM, Hung SI, Leu HB, Wu TC, Huang PH, et al. Genetic variation in renin predicts the effects of thiazide diuretics. Eur J Clin Invest 2011;41:828-35.  Back to cited text no. 27
Materson BJ, Reda DJ, Cushman WC, Massie BM, Freis ED, Kochar MS, et al. Single-drug therapy for hypertension in men. A comparison of six antihypertensive agents with placebo. The Department of Veterans Affairs Cooperative Study Group on Antihypertensive Agents. N Engl J Med 1993;328:914-21.  Back to cited text no. 28
Liu J, Liu ZQ, Yu BN, Xu FH, Mo W, Zhou G, et al. beta1-Adrenergic receptor polymorphisms influence the response to metoprolol monotherapy in patients with essential hypertension. Clin Pharmacol Ther 2006;80:23-32.  Back to cited text no. 29
Chung CM, Wang RY, Chen JW, Fann CS, Leu HB, Ho HY, et al. A genome-wide association study identifies new loci for ACE activity: Potential implications for response to ACE inhibitor. Pharmacogenomics J 2010;10:537-44.  Back to cited text no. 30
Rego-Pérez I, Fernández-Moreno M, Carreira-García V, Blanco FJ. Gene polymorphisms and pharmacogenetics in Rheumatoid Arthritis. Reumatol Clin 2009;5:268-79.  Back to cited text no. 31
Dervieux T, Furst D, Lein DO, Capps R, Smith K, Walsh M, et al. Polyglutamation of methotrexate with common polymorphisms in reduced folate carrier, aminoimidazole carboxamide ribonucleotide transformylase, and thymidylate synthase are associated with methotrexate effects in rheumatoid arthritis. Arthritis Rheum 2004;50:2766-74.  Back to cited text no. 32
Dervieux T, Kremer J, Lein DO, Capps R, Barham R, Meyer G, et al. Contribution of common polymorphisms in reduced folate carrier and gamma-glutamylhydrolase to methotrexate polyglutamate levels in patients with rheumatoid arthritis. Pharmacogenetics 2004;14:733-9.  Back to cited text no. 33
Ranganathan P, McLeod HL. Methotrexate pharmacogenetics: The first step toward individualized therapy in rheumatoid arthritis. Arthritis Rheum 2006;54:1366-77.  Back to cited text no. 34
Dervieux T. Single nucleotide polymorphisms (SNPs) in the folate/purine synthesis pathway predict methotrexate's effects in rheumatoid arthritis. Arthritis Rheum 2003;48:S438.  Back to cited text no. 35
Pawlik A, Wrzesniewska J, Fiedorowicz-Fabrycy I, Gawronska-Szklarz B. The MDR1 3435 polymorphism in patients with rheumatoid arthritis. Int J Clin Pharmacol Ther 2004;42:496-503.  Back to cited text no. 36
Fisher MC, Cronstein BN. Metaanalysis of methylenetetrahydrofolate reductase (MTHFR) polymorphisms affecting methotrexate toxicity. J Rheumatol 2009;36:539-45.  Back to cited text no. 37
Kumagai K, Hiyama K, Oyama T, Maeda H, Kohno N. Polymorphisms in the thymidylate synthase and methylenetetrahydrofolate reductase genes and sensitivity to the low-dose methotrexate therapy in patients with rheumatoid arthritis. Int J Mol Med 2003;11:593-600.  Back to cited text no. 38
Ulrich CM, Bigler J, Velicer CM, Greene EA, Farin FM, Potter JD. Searching expressed sequence tag databases: Discovery and confirmation of a common polymorphism in the thymidylate synthase gene. Cancer Epidemiol Biomarkers Prev 2000;9:1381-5.  Back to cited text no. 39
Ladero JM. Influence of polymorphic N-acetyltransferases on non-malignant spontaneous disorders and on response to drugs. Curr Drug Metab 2008;9:532-7.  Back to cited text no. 40
Sandborn WJ. Rational dosing of azathioprine and 6-mercaptopurine. Gut 2001;48:591-2.  Back to cited text no. 41
Carlini LE, Meropol NJ, Bever J, Andria ML, Hill T, Gold P, et al. UGT1A7 and UGT1A9 polymorphisms predict response and toxicity in colorectal cancer patients treated with capecitabine/irinotecan. Clin Cancer Res 2005;11:1226-36.  Back to cited text no. 42
Hoskins JM, Marcuello E, Altes A, Marsh S, Maxwell T, Van Booven DJ, et al. Irinotecan pharmacogenetics: Influence of pharmacodynamic genes. Clin Cancer Res 2008;14:1788-96.  Back to cited text no. 43
Liu X, Cheng D, Kuang Q, Liu G, Xu W. Association of UGT1A1 * 28 polymorphisms with irinotecan-induced toxicities in colorectal cancer: A meta-analysis in Caucasians. Pharmacogenomics J 2014;14:120-9.  Back to cited text no. 44
Toffoli G, Cecchin E, Corona G, Russo A, Buonadonna A, D'Andrea M, et al. The role of UGT1A1 * 28 polymorphism in the pharmacodynamics and pharmacokinetics of irinotecan in patients with metastatic colorectal cancer. J Clin Oncol 2006;24:3061-8.  Back to cited text no. 45
Iyer L, Das S, Janisch L, Wen M, Ramírez J, Karrison T, et al. UGT1A1 * 28 polymorphism as a determinant of irinotecan disposition and toxicity. Pharmacogenomics J 2002;2:43-7.  Back to cited text no. 46
Hoskins JM, Goldberg RM, Qu P, Ibrahim JG, McLeod HL. UGT1A1 * 28 genotype and irinotecan-induced neutropenia: Dose matters. J Natl Cancer Inst 2007;99:1290-5.  Back to cited text no. 47
Diasio RB. Clinical implications of dihydropyrimidine dehydrogenase on 5-FU pharmacology. Oncology (Williston Park) 2001;15:21-6.  Back to cited text no. 48
Fleming RA, Milano GA, Gaspard MH, Bargnoux PJ, Thyss A, Plagne R, et al. Dihydropyrimidine dehydrogenase activity in cancer patients. Eur J Cancer 1993;29A: 740-4.  Back to cited text no. 49
Lyss AP, Lilenbaum RC, Harris BE, Diasio RB. Severe 5-fluorouracil toxicity in a patient with decreased dihydropyrimidine dehydrogenase activity. Cancer Invest 1993;11:239-40.  Back to cited text no. 50
Schwab M, Zanger UM, Marx C, Schaeffeler E, Klein K, Dippon J, et al. Role of genetic and nongenetic factors for fluorouracil treatment-related severe toxicity: A prospective clinical trial by the German 5-FU Toxicity Study Group. J Clin Oncol 2008;26:2131-8.  Back to cited text no. 51
Houyau P, Gay C, Chatelut E, Canal P, Roché H, Milano G. Severe fluorouracil toxicity in a patient with dihydropyrimidine dehydrogenase deficiency. J Natl Cancer Inst 1993;85:1602-3.  Back to cited text no. 52
Leichman CG, Lenz HJ, Leichman L, Danenberg K, Baranda J, Groshen S, et al. Quantitation of intratumoral thymidylate synthase expression predicts for disseminated colorectal cancer response and resistance to protracted-infusion fluorouracil and weekly leucovorin. J Clin Oncol 1997;15:3223-9.  Back to cited text no. 53
Nishimura R, Nagao K, Miyayama H, Matsuda M, Baba K, Matsuoka Y, et al. Thymidylate synthase levels as a therapeutic and prognostic predictor in breast cancer. Anticancer Res 1999;19:5621-6.  Back to cited text no. 54
van Triest B, Pinedo HM, van Hensbergen Y, Smid K, Telleman F, Schoenmakers PS, et al. Thymidylate synthase level as the main predictive parameter for sensitivity to 5-fluorouracil, but not for folate-based thymidylate synthase inhibitors, in 13 nonselected colon cancer cell lines. Clin Cancer Res 1999;5:643-54.  Back to cited text no. 55
Pullarkat ST, Stoehlmacher J, Ghaderi V, Xiong YP, Ingles SA, Sherrod A, et al. Thymidylate synthase gene polymorphism determines response and toxicity of 5-FU chemotherapy. Pharmacogenomics J 2001;1:65-70.  Back to cited text no. 56
Cao H, Hegele RA. DNA polymorphisms in ITPA including basis of inosine triphosphatase deficiency. J Hum Genet 2002;47:620-2.  Back to cited text no. 57
Relling MV, Hancock ML, Rivera GK, Sandlund JT, Ribeiro RC, Krynetski EY, et al. Mercaptopurine therapy intolerance and heterozygosity at the thiopurine S-methyltransferase gene locus. J Natl Cancer Inst 1999;91:2001-8.  Back to cited text no. 58
Goetz MP, Rae JM, Suman VJ, Safgren SL, Ames MM, Visscher DW, et al. Pharmacogenetics of tamoxifen biotransformation is associated with clinical outcomes of efficacy and hot flashes. J Clin Oncol 2005;23:9312-8.  Back to cited text no. 59
McGraw J, Waller D. Cytochrome P450 variations in different ethnic populations. Expert Opin Drug Metab Toxicol 2012;8:371-82.  Back to cited text no. 60
Gattepaille LM, Jakobsson M, Blum MG. Inferring population size changes with sequence and SNP data: Lessons from human bottlenecks. Heredity (Edinb) 2013;110:409-19.  Back to cited text no. 61
Wessels JA, de Vries-Bouwstra JK, Heijmans, BT, Slagboom PE, Goekoop-Ruiterman, YP, Allaart CF, et al., Efficacy and toxicity of methotrexate in early rheumatoid arthritis are associated with single-nucleotide polymorphisms in genes coding for folate pathway enzymes. Arthritis & Rheumatism, 2006;54:1087-95.  Back to cited text no. 62
Evans WE. Differing effects of methylenetetrahydrofolate reductase single nucleotide polymorphisms on methotrexate efficacy and toxicity in rheumatoid arthritis. Pharmacogenetics and Genomics, 2002;12:181-2.  Back to cited text no. 63


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