| Literature DB >> 32936528 |
Pablo Zubiaur1,2, Dora Koller1, Miriam Saiz-Rodríguez1,3, Marcos Navares-Gómez1, Francisco Abad-Santos1,2,4.
Abstract
In December 2019, the severe acute respiratory syndrome virus-2 pandemic began, causing the coronavirus disease 2019. A vast variety of drugs is being used off-label as potential therapies. Many of the repurposed drugs have clinical pharmacogenetic guidelines available with therapeutic recommendations when prescribed as indicated on the drug label. The aim of this review is to provide a comprehensive summary of pharmacogenetic biomarkers available for these drugs, which may help to prescribe them more safely.Entities:
Year: 2020 PMID: 32936528 PMCID: PMC7719396 DOI: 10.1111/cts.12866
Source DB: PubMed Journal: Clin Transl Sci ISSN: 1752-8054 Impact factor: 4.689
Figure 1Levels of evidence for the pharmacogenetic testing and application of clinical recommendations for drugs used in the treatment of coronavirus disease 2019 and percentage of drugs per evidence level.
Summary of drugs used during COVID‐19 pandemic with corresponding pharmacogenetic information
| Drug | Biomarker | Level of evidence |
|---|---|---|
| Chloroquine and hydroxychloroquine |
| 2 |
|
| 4 | |
| Remdesivir |
| 4 |
| Losartan |
| 3 |
| Captopril, enalapril, and lisinopril | ACE rs1799752 | 3 |
| Spironolactone |
| 3 |
| Ribavirin and peg‐interferon alfa 2a/2b |
| 1 |
| Lopinavir/ritonavir | CYP3A4 | 4 |
| Atazanavir/ritonavir |
| 1 |
| Corticosteroids |
| 3 |
| Progesterone |
| 3 |
| Nonsteroidal anti‐inflammatory drugs |
| 1 |
| Tocilizumab |
| 3 |
|
| 4 | |
| Sarilumab |
| 4 |
|
| 4 | |
| Siltuximab |
| 4 |
|
| 4 | |
| Sirolimus |
| 3 |
| Nicotine |
| 3 |
| Fluvoxamine |
| 1 |
| Ruxolitinib |
| 4 |
| Baricitinib |
| 4 |
| Anakinra |
| 3 |
| Colchicine |
| 3 |
Levels of evidence. 1: Biomarkers with clinical pharmacogenetic guidelines; 2: Biomarkers with clinical pharmacogenetic guidelines applied to other drugs; 3: Candidate pharmacogenetic biomarkers as published in peer‐review journals without clinical pharmacogenetic guidelines; 4: Speculative biomarkers.
ABCB1, ATP binding cassette subfamily B member 1; ACE, angiotensin‐converting enzyme; ADD1, adducin 1 (alpha); COVID‐19, coronavirus disease 2019; CYP, cytochrome P450; G6PD, glucose‐6‐phosphate dehydrogenase; IFNL3, interferon lambda 3; IL‐1, interleukin‐1; IL‐6R, interleukin‐6 receptor; UGT1A1, UDP glucuronosyltransferase family 1 member A1.
UGT1A1 phenotype inference based on genotype information
| UGT1A1 | |
|---|---|
| Normal metabolizers | |
| *1/*1, *1/*36, *36/*36 | 2 reference function (*1/*1) and/or increased function allele (*36) |
| rs887829 C/C | rs887829 C/C homozygosity |
| Intermediate metabolizers | |
| *1/*28, *1/*37, *36/*28, *36/*37 | 1 reference function (*1) or increased function allele (*36) and 1 decreased function allele (*6, *28, *37) |
| rs887829 C/T (*1/*80) | rs887829 C/T heterozygosity |
| Poor metabolizers | |
| *28/*28, *28/*37, *37/*37, *6/*6 | 2 decreased function alleles (*6, *28, *37). |
| rs887829 T/T (*80/*80) | rs887829 T/T homozygosity |
Information obtained from Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline on atazanavir and UGT1A1.
UGT1A1, UDP glucuronosyltransferase family 1 member A1.
CYP2C9 phenotype inference based on genotype information
| CYP2C9 | ||
|---|---|---|
| Normal metabolizers | ||
| AS = 2.0 | *1/*1 | 2 normal‐function alleles |
| Intermediate metabolizers | ||
| AS = 1.5 | *1/*2, *1/*5, 1*/*8, *1/*11 | 1 normal‐function allele + 1 decreased‐function allele |
| AS = 1.0 | *1/*3, *2/*2, *2/*5, *2/*8, *2/*11, *5/*5, *5/*8, *5/*11, *8/*8, *8/11, *11/11 | 1 normal‐function allele + 1 decreased‐function allele or 2 decreased‐function alleles |
| Poor metabolizers | ||
| AS = 0.5 | *2/*3, *3/*5, 3*/*8, *3/*11 | 1 decreased‐function allele + 1 no‐function allele |
| AS = 0 | *3/*3 | 2 no‐function alleles |
Information obtained from Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline on non‐steroidal anti‐inflammatory drugs and CYP2C9.
AS, activity score; CYP2C9, cytochrome P450 2C9.
CYP2D6 phenotype inference based on genotype information
| CYP2D6 | ||
|---|---|---|
| Ultrarapid metabolizers | ||
| AS > 2.25 |
*1/*1xN, *1/*2xN, *2/*2xN *1x2/*9 |
Duplicated normal function alleles in combination with (1) a decreased function allele other than (2) another normal function allele |
| Normal metabolizers | ||
| AS = 2.25 | *1x2/*10, *2x2/*10 | Duplicated normal function alleles in combination with |
| AS = 2.0 | *1/*1, *1/*2 | 2 normal function alleles |
| AS = 1.5 | *1/*41, *1/*9 | A normal function allele plus a decreased function allele other than |
| AS = 1.25 | *1/*10 |
|
| Intermediate metabolizers | ||
| AS = 1.0 | *41/*41, *1/*5 | 2 decreased function alleles other than |
| AS = 0.75 | *9/*10, *10/*41 |
|
| AS = 0.5 | *4/*41, *10/*10 |
|
| AS = 0.25 | *4/*10 |
|
| Poor metabolizers | ||
| AS = 0 | *3/*4, *4/*4, *5/*5, *5/*6 | 2 no function alleles |
Information obtained from Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group standardizing consensus on CYP2D6 genotype to phenotype translation.
AS, activity score; CYP2D6, cytochrome P450 2D6.