| Literature DB >> 31749990 |
Jessie Sun1, Steven R Tung2, Danxin Wang3, Joseph P Kitzmiller4,5, Sakima Smith6.
Abstract
Much of the recent gains in knowledge regarding the influence of patient genetics on medication pharmacokinetics (drug absorption, distribution, metabolism and elimination) how patients process medications) and pharmacodynamics (drug response) have been attributed to the technologic advances in genetic testing methodologies and the involvement of large clinical data sets and biobanks. Indeed, Genome Wide Association Studies (GWAS) and Phenome Wide Association Studies (PWAS) along with ever-evolving biomedical informatics techniques and the expansion of the -omics sciences (e.g., transcriptomics, metabolomics, proteomics) have brought about unprecedented advances in precision medicine. Although the simpler candidate-gene analysis technique is not considered cutting-edge, it is reliable and important to the translation of pharmacogenomic research and the advancement of precision medicine. Leveraging the knowledge of biological plausibility (i.e., genetic mutation → altered function of protein product → altered drug pharmacokinetics/dynamics) to appropriately select genes for inclusion, the candidate-gene analysis technique does not necessitate large patient cohorts nor extensive multi-gene genetic analysis arrays. It is often the ideal method for clinicians to begin evaluating whether genetic information might improve their pharmacologic treatment strategies for their patients. Having access to specific patient populations and expertise regarding their medical subspecialty, physician scientists can implement a candidate-gene analysis in small cohorts. Even with less than 100 patients, results can often be used to determine whether further investigation is warranted and to inform future studies. Herein, we present a comparison of select contemporary methodologies regarding collection, processing and genotype testing applicable to the efficient implementation of candidate-gene studies.Entities:
Year: 2018 PMID: 31749990 PMCID: PMC6867604 DOI: 10.15761/JTS.1000306
Source DB: PubMed Journal: J Transl Sci
Figure 1.Comparison of cost per unit for methods 1–6 for both 100 units and 2000 units. Methods 7 and 8 were not included in the comparison since they were the same costs as methods 2 and 3
Figure 2.Comparison of average DNA yield for each method. Method 1 had the greatest yield and Method 4 had the least yield
Method, stabilization buffer, and extraction protocols used
| Method | Stabilization Buffer | Extraction Protocols |
|---|---|---|
| 1 | Goode et al. | Goode et al. |
| 2 | Oragene Discover | Oragene Discover |
| 3 | Norgen Biotek | Norgen Biotek |
| 4 | Acceqen Aceseq | Zymo Quick-DNA |
| 5 | Oasis SimplOFy | Zymo Quick-DNA |
| 6 | Goode et al. | Zymo Quick-DNA |
| 7 | Oragene Discover | Zymo Quick-DNA |
| 8 | Norgen Biotek | Zymo Quick-DNA |
A comparison of Yield, Cost and Time data for the eight Methods
| Method | Stabilization Buffer | Extraction Method | Yield (ng/μL) | Cost: 100 Units | Cost/Unit | Cost: 2000 Units | Cost/Unit | Time (min) |
|---|---|---|---|---|---|---|---|---|
| 1 | Goode, | Goode, | 78.45 | $ 2,274.67 | $ 22.75 | $ 22,016.49 | $ 11.01 | 150 |
| 2 | Oragene Discover | Oragene | 15.65 | $ 2,141.91 | $ 21.42 | $ 31,507.91 | $ 15.75 | 90 |
| 3 | Norgen Biotek | Norgen | 26.80 | $ 1,650.56 | $ 16.51 | $ 21,065.56 | $ 10.53 | 20 |
| 4 | Accegen Aceseq | Zymo Quick-DNA | 3.21 | $ 1,615.00 | $ 16.15 | $ 21,800.00 | $ 10.90 | 20 |
| 5 | Oasis SimplOFy | Zymo Quick-DNA | 10.71 | $ 1,488.00 | $ 14.88 | $ 26,324.00 | $ 13.16 | 60 |
| 6 | Goode, | Zymo Quick-DNA | 21.15 | $ 967.61 | $ 9.68 | $ 6,966.31 | $ 3.48 | 30 |
| 7 | Oragene Discover | Zymo Quick-DNA | - | $ 2,468.91 | $ 24.69 | $ 36,901.91 | $ 18.45 | 30 |
| 8 | Norgen Biotek | Zymo Quick-DNA | 1.40 | $ 1,877.56 | $ 19.78 | $ 26,459.59 | $ 13.23 | 30 |
Figure 3.Amplification of DNA after cycles of PCR. All samples displayed similar amplification plots independent of DNA yield quantity