dbSNP Short Genetic Variations
Welcome to the Reference SNP (rs) Report
All alleles are reported in the Forward orientation. Click on the Variant Details tab for details on Genomic Placement, Gene, and Amino Acid changes. HGVS names are in the HGVS tab.
Reference SNP (rs) Report
This page reports data for a single dbSNP Reference SNP variation (RefSNP or rs) from the new redesigned dbSNP build.
Top of the page reports a concise summary for the rs, with more specific details included in the corresponding tabs below.
All alleles are reported in the Forward orientation. Use the Genomic View to inspect the nucleotides flanking the variant, and its neighbors.
For more information see Help documentation.
rs1142345
Current Build 157
Released September 3, 2024
- Organism
- Homo sapiens
- Position
-
chr6:18130687 (GRCh38.p14) Help
The anchor position for this RefSNP. Includes all nucleotides potentially affected by this change, thus it can differ from HGVS, which is right-shifted. See here for details.
- Alleles
- T>A / T>C / T>G
- Variation Type
- SNV Single Nucleotide Variation
- Frequency
-
C=0.0430740 (60164/1396758, GnomAD_exomes)C=0.045710 (12099/264690, TOPMED)C=0.040902 (10610/259402, ALFA) (+ 24 more)
- Clinical Significance
- Reported in ClinVar
- Gene : Consequence
- TPMT : Missense Variant
- Publications
- 92 citations
- Genomic View
- See rs on genome
ALFA Allele Frequency
The ALFA project provide aggregate allele frequency from dbGaP. More information is available on the project page including descriptions, data access, and terms of use.
Population | Group | Sample Size | Ref Allele | Alt Allele | Ref HMOZ | Alt HMOZ | HTRZ | HWEP |
---|---|---|---|---|---|---|---|---|
Total | Global | 259402 | T=0.959098 | C=0.040902 | 0.920109 | 0.001912 | 0.077979 | 3 |
European | Sub | 213762 | T=0.958968 | C=0.041032 | 0.919799 | 0.001862 | 0.078339 | 1 |
African | Sub | 11822 | T=0.94510 | C=0.05490 | 0.893081 | 0.002876 | 0.104043 | 0 |
African Others | Sub | 426 | T=0.934 | C=0.066 | 0.873239 | 0.004695 | 0.122066 | 0 |
African American | Sub | 11396 | T=0.94551 | C=0.05449 | 0.893822 | 0.002808 | 0.10337 | 0 |
Asian | Sub | 6720 | T=0.9836 | C=0.0164 | 0.968155 | 0.000893 | 0.030952 | 3 |
East Asian | Sub | 4830 | T=0.9824 | C=0.0176 | 0.966046 | 0.001242 | 0.032712 | 4 |
Other Asian | Sub | 1890 | T=0.9868 | C=0.0132 | 0.973545 | 0.0 | 0.026455 | 0 |
Latin American 1 | Sub | 1232 | T=0.9586 | C=0.0414 | 0.920455 | 0.003247 | 0.076299 | 1 |
Latin American 2 | Sub | 5254 | T=0.9477 | C=0.0523 | 0.900266 | 0.004949 | 0.094785 | 3 |
South Asian | Sub | 344 | T=0.980 | C=0.020 | 0.959302 | 0.0 | 0.040698 | 0 |
Other | Sub | 20268 | T=0.96314 | C=0.03686 | 0.927669 | 0.001381 | 0.070949 | 0 |
Frequency tab displays a table of the reference and alternate allele frequencies reported by various studies and populations. Table lines, where Population="Global" refer to the entire study population, whereas lines, where Group="Sub", refer to a study-specific population subgroupings (i.e. AFR, CAU, etc.), if available. Frequency for the alternate allele (Alt Allele) is a ratio of samples observed-to-total, where the numerator (observed samples) is the number of chromosomes in the study with the minor allele present (found in "Sample size", where Group="Sub"), and the denominator (total samples) is the total number of all chromosomes in the study for the variant (found in "Sample size", where Group="Study-wide" and Population="Global").
DownloadStudy | Population | Group | Sample Size | Ref Allele | Alt Allele |
---|---|---|---|---|---|
gnomAD v4 - Exomes | Global | Study-wide | 1396758 | T=0.9569260 | C=0.0430740 |
gnomAD v4 - Exomes | European | Sub | 1162240 | T=0.9537634 | C=0.0462366 |
gnomAD v4 - Exomes | South Asian | Sub | 86114 | T=0.98327 | C=0.01673 |
gnomAD v4 - Exomes | American | Sub | 44710 | T=0.95151 | C=0.04849 |
gnomAD v4 - Exomes | East Asian | Sub | 39624 | T=0.98703 | C=0.01297 |
gnomAD v4 - Exomes | African | Sub | 33360 | T=0.94469 | C=0.05531 |
gnomAD v4 - Exomes | Ashkenazi Jewish | Sub | 26100 | T=0.98429 | C=0.01571 |
gnomAD v4 - Exomes | Middle Eastern | sub | 4610 | T=0.9896 | C=0.0104 |
TopMed | Global | Study-wide | 264690 | T=0.954290 | C=0.045710 |
Allele Frequency Aggregator | Total | Global | 259402 | T=0.959098 | C=0.040902 |
Allele Frequency Aggregator | European | Sub | 213762 | T=0.958968 | C=0.041032 |
Allele Frequency Aggregator | Other | Sub | 20268 | T=0.96314 | C=0.03686 |
Allele Frequency Aggregator | African | Sub | 11822 | T=0.94510 | C=0.05490 |
Allele Frequency Aggregator | Asian | Sub | 6720 | T=0.9836 | C=0.0164 |
Allele Frequency Aggregator | Latin American 2 | Sub | 5254 | T=0.9477 | C=0.0523 |
Allele Frequency Aggregator | Latin American 1 | Sub | 1232 | T=0.9586 | C=0.0414 |
Allele Frequency Aggregator | South Asian | Sub | 344 | T=0.980 | C=0.020 |
gnomAD v4 - Genomes | Global | Study-wide | 149290 | T=0.956595 | C=0.043405 |
gnomAD v4 - Genomes | European | Sub | 78648 | T=0.95948 | C=0.04052 |
gnomAD v4 - Genomes | African | Sub | 41560 | T=0.94497 | C=0.05503 |
gnomAD v4 - Genomes | American | Sub | 15304 | T=0.94949 | C=0.05051 |
gnomAD v4 - Genomes | East Asian | Sub | 5186 | T=0.9863 | C=0.0137 |
gnomAD v4 - Genomes | South Asian | Sub | 4828 | T=0.9812 | C=0.0188 |
gnomAD v4 - Genomes | Ashkenazi Jewish | Sub | 3470 | T=0.9810 | C=0.0190 |
gnomAD v4 - Genomes | Middle Eastern | sub | 294 | T=0.983 | C=0.017 |
ExAC | Global | Study-wide | 120882 | T=0.963311 | C=0.036689 |
ExAC | Europe | Sub | 73188 | T=0.96044 | C=0.03956 |
ExAC | Asian | Sub | 25142 | T=0.98373 | C=0.01627 |
ExAC | American | Sub | 11546 | T=0.95193 | C=0.04807 |
ExAC | African | Sub | 10106 | T=0.94587 | C=0.05413 |
ExAC | Other | Sub | 900 | T=0.968 | C=0.032 |
38KJPN | JAPANESE | Study-wide | 77444 | T=0.99039 | C=0.00961 |
Korean Genome Project 4K | KOREAN | Study-wide | 7234 | T=0.9837 | C=0.0163 |
1000Genomes_30X | Global | Study-wide | 6404 | T=0.9603 | C=0.0397 |
1000Genomes_30X | African | Sub | 1786 | T=0.9401 | C=0.0599 |
1000Genomes_30X | Europe | Sub | 1266 | T=0.9700 | C=0.0300 |
1000Genomes_30X | South Asian | Sub | 1202 | T=0.9834 | C=0.0166 |
1000Genomes_30X | East Asian | Sub | 1170 | T=0.9778 | C=0.0222 |
1000Genomes_30X | American | Sub | 980 | T=0.936 | C=0.064 |
1000Genomes | Global | Study-wide | 5008 | T=0.9609 | C=0.0391 |
1000Genomes | African | Sub | 1322 | T=0.9334 | C=0.0666 |
1000Genomes | East Asian | Sub | 1008 | T=0.9782 | C=0.0218 |
1000Genomes | Europe | Sub | 1006 | T=0.9712 | C=0.0288 |
1000Genomes | South Asian | Sub | 978 | T=0.983 | C=0.017 |
1000Genomes | American | Sub | 694 | T=0.942 | C=0.058 |
The Avon Longitudinal Study of Parents and Children | PARENT AND CHILD COHORT | Study-wide | 3854 | T=0.9543 | C=0.0457 |
UK 10K study - Twins | TWIN COHORT | Study-wide | 3708 | T=0.9493 | C=0.0507 |
MxGDAR/Encodat-PGx | Global | Study-wide | 3230 | T=0.9517 | C=0.0483 |
MxGDAR/Encodat-PGx | MxGDAR | Sub | 3230 | T=0.9517 | C=0.0483 |
KOREAN population from KRGDB | KOREAN | Study-wide | 2930 | T=0.9843 | C=0.0157 |
HapMap | Global | Study-wide | 1890 | T=0.9630 | C=0.0370 |
HapMap | American | Sub | 770 | T=0.962 | C=0.038 |
HapMap | African | Sub | 690 | T=0.946 | C=0.054 |
HapMap | Asian | Sub | 254 | T=0.988 | C=0.012 |
HapMap | Europe | Sub | 176 | T=0.994 | C=0.006 |
Korean Genome Project | KOREAN | Study-wide | 1832 | T=0.9814 | C=0.0186 |
Genome of the Netherlands Release 5 | Genome of the Netherlands | Study-wide | 998 | T=0.958 | C=0.042 |
PharmGKB Aggregated | Global | Study-wide | 674 | T=0.945 | C=0.055 |
PharmGKB Aggregated | PA148721079 | Sub | 354 | T=0.960 | C=0.040 |
PharmGKB Aggregated | PA130416061 | Sub | 180 | T=0.917 | C=0.083 |
PharmGKB Aggregated | PA142188328 | Sub | 140 | T=0.943 | C=0.057 |
A Vietnamese Genetic Variation Database | Global | Study-wide | 614 | T=0.974 | C=0.026 |
Northern Sweden | ACPOP | Study-wide | 600 | T=0.970 | C=0.030 |
Medical Genome Project healthy controls from Spanish population | Spanish controls | Study-wide | 534 | T=0.966 | C=0.034 |
FINRISK | Finnish from FINRISK project | Study-wide | 304 | T=0.980 | C=0.020 |
Qatari | Global | Study-wide | 216 | T=0.995 | C=0.005 |
The Danish reference pan genome | Danish | Study-wide | 40 | T=0.95 | C=0.05 |
SGDP_PRJ | Global | Study-wide | 28 | T=0.50 | C=0.50 |
Siberian | Global | Study-wide | 6 | T=0.5 | C=0.5 |
Variant Details tab shows known variant placements on genomic sequences: chromosomes (NC_), RefSeqGene, pseudogenes or genomic regions (NG_), and in a separate table: on transcripts (NM_) and protein sequences (NP_). The corresponding transcript and protein locations are listed in adjacent lines, along with molecular consequences from Sequence Ontology. When no protein placement is available, only the transcript is listed. Column "Codon[Amino acid]" shows the actual base change in the format of "Reference > Alternate" allele, including the nucleotide codon change in transcripts, and the amino acid change in proteins, respectively, allowing for known ribosomal slippage sites. To view nucleotides adjacent to the variant use the Genomic View at the bottom of the page - zoom into the sequence until the nucleotides around the variant become visible.
Sequence name | Change |
---|---|
GRCh38.p14 chr 6 | NC_000006.12:g.18130687T>A |
GRCh38.p14 chr 6 | NC_000006.12:g.18130687T>C |
GRCh38.p14 chr 6 | NC_000006.12:g.18130687T>G |
GRCh37.p13 chr 6 | NC_000006.11:g.18130918T>A |
GRCh37.p13 chr 6 | NC_000006.11:g.18130918T>C |
GRCh37.p13 chr 6 | NC_000006.11:g.18130918T>G |
TPMT RefSeqGene (LRG_874) | NG_012137.3:g.29457A>T |
TPMT RefSeqGene (LRG_874) | NG_012137.3:g.29457A>G |
TPMT RefSeqGene (LRG_874) | NG_012137.3:g.29457A>C |
Molecule type | Change | Amino acid[Codon] | SO Term |
---|---|---|---|
TPMT transcript variant 2 | NM_001346817.1:c.719A>T | Y [TAT] > F [TTT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_001333746.1:p.Tyr240Phe | Y (Tyr) > F (Phe) | Missense Variant |
TPMT transcript variant 2 | NM_001346817.1:c.719A>G | Y [TAT] > C [TGT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_001333746.1:p.Tyr240Cys | Y (Tyr) > C (Cys) | Missense Variant |
TPMT transcript variant 2 | NM_001346817.1:c.719A>C | Y [TAT] > S [TCT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_001333746.1:p.Tyr240Ser | Y (Tyr) > S (Ser) | Missense Variant |
TPMT transcript variant 3 | NM_001346818.1:c.674A>T | Y [TAT] > F [TTT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 2 | NP_001333747.1:p.Tyr225Phe | Y (Tyr) > F (Phe) | Missense Variant |
TPMT transcript variant 3 | NM_001346818.1:c.674A>G | Y [TAT] > C [TGT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 2 | NP_001333747.1:p.Tyr225Cys | Y (Tyr) > C (Cys) | Missense Variant |
TPMT transcript variant 3 | NM_001346818.1:c.674A>C | Y [TAT] > S [TCT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 2 | NP_001333747.1:p.Tyr225Ser | Y (Tyr) > S (Ser) | Missense Variant |
TPMT transcript variant 1 | NM_000367.5:c.719A>T | Y [TAT] > F [TTT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_000358.1:p.Tyr240Phe | Y (Tyr) > F (Phe) | Missense Variant |
TPMT transcript variant 1 | NM_000367.5:c.719A>G | Y [TAT] > C [TGT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_000358.1:p.Tyr240Cys | Y (Tyr) > C (Cys) | Missense Variant |
TPMT transcript variant 1 | NM_000367.5:c.719A>C | Y [TAT] > S [TCT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform 1 | NP_000358.1:p.Tyr240Ser | Y (Tyr) > S (Ser) | Missense Variant |
TPMT transcript variant X1 | XM_047419289.1:c.719A>T | Y [TAT] > F [TTT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X1 | XP_047275245.1:p.Tyr240Phe | Y (Tyr) > F (Phe) | Missense Variant |
TPMT transcript variant X1 | XM_047419289.1:c.719A>G | Y [TAT] > C [TGT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X1 | XP_047275245.1:p.Tyr240Cys | Y (Tyr) > C (Cys) | Missense Variant |
TPMT transcript variant X1 | XM_047419289.1:c.719A>C | Y [TAT] > S [TCT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X1 | XP_047275245.1:p.Tyr240Ser | Y (Tyr) > S (Ser) | Missense Variant |
TPMT transcript variant X2 | XM_047419290.1:c.674A>T | Y [TAT] > F [TTT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X2 | XP_047275246.1:p.Tyr225Phe | Y (Tyr) > F (Phe) | Missense Variant |
TPMT transcript variant X2 | XM_047419290.1:c.674A>G | Y [TAT] > C [TGT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X2 | XP_047275246.1:p.Tyr225Cys | Y (Tyr) > C (Cys) | Missense Variant |
TPMT transcript variant X2 | XM_047419290.1:c.674A>C | Y [TAT] > S [TCT] | Coding Sequence Variant |
thiopurine S-methyltransferase isoform X2 | XP_047275246.1:p.Tyr225Ser | Y (Tyr) > S (Ser) | Missense Variant |
Clinical Significance tab shows a list of clinical significance entries from ClinVar associated with the variation, per allele. Click on the RCV accession (i.e. RCV000001615.2) or Allele ID (i.e. 12274) to access full ClinVar report.
ClinVar Accession | Disease Names | Clinical Significance |
---|---|---|
RCV000013559.35 | Thiopurine S-methyltransferase deficiency | Drug-Response |
RCV000013562.32 | Thiopurine S-methyltransferase deficiency | Drug-Response |
RCV000396233.15 | not provided | Likely-Benign,Other |
Aliases tab displays HGVS names representing the variant placements and allele changes on genomic, transcript and protein sequences, per allele. HGVS name is an expression for reporting sequence accession and version, sequence type, position, and allele change. The column "Note" can have two values: "diff" means that there is a difference between the reference allele (variation interval) at the placement reported in HGVS name and the reference alleles reported in other HGVS names, and "rev" means that the sequence of this variation interval at the placement reported in HGVS name is in reverse orientation to the sequence(s) of this variation in other HGVS names not labeled as "rev".
Placement | T= | A | C | G |
---|---|---|---|---|
GRCh38.p14 chr 6 | NC_000006.12:g.18130687= | NC_000006.12:g.18130687T>A | NC_000006.12:g.18130687T>C | NC_000006.12:g.18130687T>G |
GRCh37.p13 chr 6 | NC_000006.11:g.18130918= | NC_000006.11:g.18130918T>A | NC_000006.11:g.18130918T>C | NC_000006.11:g.18130918T>G |
TPMT RefSeqGene (LRG_874) | NG_012137.3:g.29457= | NG_012137.3:g.29457A>T | NG_012137.3:g.29457A>G | NG_012137.3:g.29457A>C |
TPMT transcript variant 1 | NM_000367.5:c.719= | NM_000367.5:c.719A>T | NM_000367.5:c.719A>G | NM_000367.5:c.719A>C |
TPMT transcript variant 1 | NM_000367.4:c.719= | NM_000367.4:c.719A>T | NM_000367.4:c.719A>G | NM_000367.4:c.719A>C |
TPMT transcript | NM_000367.3:c.719= | NM_000367.3:c.719A>T | NM_000367.3:c.719A>G | NM_000367.3:c.719A>C |
TPMT transcript | NM_000367.2:c.719= | NM_000367.2:c.719A>T | NM_000367.2:c.719A>G | NM_000367.2:c.719A>C |
TPMT transcript variant 2 | NM_001346817.1:c.719= | NM_001346817.1:c.719A>T | NM_001346817.1:c.719A>G | NM_001346817.1:c.719A>C |
TPMT transcript variant 3 | NM_001346818.1:c.674= | NM_001346818.1:c.674A>T | NM_001346818.1:c.674A>G | NM_001346818.1:c.674A>C |
TPMT transcript variant X1 | XM_047419289.1:c.719= | XM_047419289.1:c.719A>T | XM_047419289.1:c.719A>G | XM_047419289.1:c.719A>C |
TPMT transcript variant X2 | XM_047419290.1:c.674= | XM_047419290.1:c.674A>T | XM_047419290.1:c.674A>G | XM_047419290.1:c.674A>C |
thiopurine S-methyltransferase isoform 1 | NP_000358.1:p.Tyr240= | NP_000358.1:p.Tyr240Phe | NP_000358.1:p.Tyr240Cys | NP_000358.1:p.Tyr240Ser |
thiopurine S-methyltransferase isoform 1 | NP_001333746.1:p.Tyr240= | NP_001333746.1:p.Tyr240Phe | NP_001333746.1:p.Tyr240Cys | NP_001333746.1:p.Tyr240Ser |
thiopurine S-methyltransferase isoform 2 | NP_001333747.1:p.Tyr225= | NP_001333747.1:p.Tyr225Phe | NP_001333747.1:p.Tyr225Cys | NP_001333747.1:p.Tyr225Ser |
thiopurine S-methyltransferase isoform X1 | XP_047275245.1:p.Tyr240= | XP_047275245.1:p.Tyr240Phe | XP_047275245.1:p.Tyr240Cys | XP_047275245.1:p.Tyr240Ser |
thiopurine S-methyltransferase isoform X2 | XP_047275246.1:p.Tyr225= | XP_047275246.1:p.Tyr225Phe | XP_047275246.1:p.Tyr225Cys | XP_047275246.1:p.Tyr225Ser |
Submissions tab displays variations originally submitted to dbSNP, now supporting this RefSNP cluster (rs). We display Submitter handle, Submission identifier, Date and Build number, when the submission appeared for the first time. Direct submissions to dbSNP have Submission ID in the form of an ss-prefixed number (ss#). Other supporting variations are listed in the table without ss#.
No | Submitter | Submission ID | Date (Build) |
---|---|---|---|
1 | LEE | ss1554460 | Oct 13, 2000 (86) |
2 | HGBASE | ss2421439 | Nov 14, 2000 (94) |
3 | PHARMGKB_PAAR-SJCRH | ss69368192 | May 16, 2007 (127) |
4 | PHARMGKB_PPII | ss69370567 | May 16, 2007 (127) |
5 | AFFY | ss74811830 | Aug 16, 2007 (128) |
6 | AFFY | ss74822055 | Aug 16, 2007 (128) |
7 | ILLUMINA | ss75279105 | Dec 07, 2007 (129) |
8 | ILLUMINA | ss75287553 | Dec 07, 2007 (129) |
9 | CGM_KYOTO | ss76875486 | Dec 07, 2007 (129) |
10 | PHARMGKB_AB_DME | ss84164450 | Dec 16, 2007 (130) |
11 | SNP500CANCER | ss105439122 | Feb 06, 2009 (130) |
12 | KRIBB_YJKIM | ss119383576 | Dec 01, 2009 (131) |
13 | ILLUMINA | ss123105575 | Dec 01, 2009 (131) |
14 | ILLUMINA | ss123336313 | Dec 01, 2009 (131) |
15 | ILLUMINA | ss159977692 | Dec 01, 2009 (131) |
16 | 1000GENOMES | ss240424863 | Jul 15, 2010 (132) |
17 | OMICIA | ss244238585 | Aug 29, 2012 (137) |
18 | ILLUMINA | ss244272401 | Jul 04, 2010 (132) |
19 | OMIM-CURATED-RECORDS | ss275515909 | Nov 29, 2010 (133) |
20 | NHLBI-ESP | ss342202115 | May 09, 2011 (134) |
21 | ILLUMINA | ss479976551 | Sep 08, 2015 (146) |
22 | 1000GENOMES | ss490920222 | May 04, 2012 (137) |
23 | EXOME_CHIP | ss491378155 | May 04, 2012 (137) |
24 | CLINSEQ_SNP | ss491881231 | May 04, 2012 (137) |
25 | ILLUMINA | ss534203861 | Sep 08, 2015 (146) |
26 | SSMP | ss652948628 | Apr 25, 2013 (138) |
27 | ILLUMINA | ss780845863 | Sep 08, 2015 (146) |
28 | ILLUMINA | ss783529410 | Sep 08, 2015 (146) |
29 | ILLUMINA | ss825644720 | Apr 01, 2015 (144) |
30 | QEHCHEMPATH | ss831883150 | Mar 15, 2016 (147) |
31 | JMKIDD_LAB | ss974458968 | Aug 21, 2014 (142) |
32 | EVA-GONL | ss982638248 | Aug 21, 2014 (142) |
33 | JMKIDD_LAB | ss1067475581 | Aug 21, 2014 (142) |
34 | JMKIDD_LAB | ss1073420853 | Aug 21, 2014 (142) |
35 | 1000GENOMES | ss1319172549 | Aug 21, 2014 (142) |
36 | EVA_GENOME_DK | ss1581553289 | Apr 01, 2015 (144) |
37 | EVA_FINRISK | ss1584043919 | Apr 01, 2015 (144) |
38 | EVA_DECODE | ss1592188623 | Apr 01, 2015 (144) |
39 | EVA_UK10K_ALSPAC | ss1615060464 | Apr 01, 2015 (144) |
40 | EVA_UK10K_TWINSUK | ss1658054497 | Apr 01, 2015 (144) |
41 | EVA_EXAC | ss1688172336 | Apr 01, 2015 (144) |
42 | EVA_MGP | ss1711113284 | Apr 01, 2015 (144) |
43 | EVA_SVP | ss1712840126 | Apr 01, 2015 (144) |
44 | ILLUMINA | ss1752617943 | Sep 08, 2015 (146) |
45 | HAMMER_LAB | ss1804304017 | Sep 08, 2015 (146) |
46 | ILLUMINA | ss1917799662 | Feb 12, 2016 (147) |
47 | WEILL_CORNELL_DGM | ss1925894401 | Feb 12, 2016 (147) |
48 | ILLUMINA | ss1946168662 | Feb 12, 2016 (147) |
49 | ILLUMINA | ss1958867439 | Feb 12, 2016 (147) |
50 | AMU | ss1966656270 | Feb 12, 2016 (147) |
51 | JJLAB | ss2023565669 | Sep 14, 2016 (149) |
52 | ILLUMINA | ss2094820454 | Dec 20, 2016 (150) |
53 | USC_VALOUEV | ss2151730016 | Dec 20, 2016 (150) |
54 | ILLUMINA | ss2634407225 | Nov 08, 2017 (151) |
55 | ILLUMINA | ss2634407226 | Nov 08, 2017 (151) |
56 | GRF | ss2707318195 | Nov 08, 2017 (151) |
57 | ILLUMINA | ss2711061327 | Nov 08, 2017 (151) |
58 | GNOMAD | ss2735561433 | Nov 08, 2017 (151) |
59 | GNOMAD | ss2747554041 | Nov 08, 2017 (151) |
60 | GNOMAD | ss2836353081 | Nov 08, 2017 (151) |
61 | AFFY | ss2985984175 | Nov 08, 2017 (151) |
62 | SWEGEN | ss2998599174 | Nov 08, 2017 (151) |
63 | ILLUMINA | ss3022579689 | Nov 08, 2017 (151) |
64 | KOEX | ss3029664475 | Nov 08, 2017 (151) |
65 | CSHL | ss3346859984 | Nov 08, 2017 (151) |
66 | ILLUMINA | ss3629456166 | Oct 12, 2018 (152) |
67 | ILLUMINA | ss3629456167 | Oct 12, 2018 (152) |
68 | ILLUMINA | ss3635046782 | Oct 12, 2018 (152) |
69 | ILLUMINA | ss3636761940 | Oct 12, 2018 (152) |
70 | ILLUMINA | ss3640754078 | Oct 12, 2018 (152) |
71 | ILLUMINA | ss3643551623 | Oct 12, 2018 (152) |
72 | ILLUMINA | ss3644901726 | Oct 12, 2018 (152) |
73 | OMUKHERJEE_ADBS | ss3646331127 | Oct 12, 2018 (152) |
74 | ILLUMINA | ss3653088303 | Oct 12, 2018 (152) |
75 | EVA_DECODE | ss3716687250 | Jul 13, 2019 (153) |
76 | ILLUMINA | ss3726314857 | Jul 13, 2019 (153) |
77 | ACPOP | ss3733249912 | Jul 13, 2019 (153) |
78 | ILLUMINA | ss3744546291 | Jul 13, 2019 (153) |
79 | ILLUMINA | ss3745346868 | Jul 13, 2019 (153) |
80 | EVA | ss3764676098 | Jul 13, 2019 (153) |
81 | ILLUMINA | ss3772840657 | Jul 13, 2019 (153) |
82 | KHV_HUMAN_GENOMES | ss3807838503 | Jul 13, 2019 (153) |
83 | EVA | ss3824158467 | Apr 26, 2020 (154) |
84 | EVA | ss3825690598 | Apr 26, 2020 (154) |
85 | EVA | ss3829760076 | Apr 26, 2020 (154) |
86 | SGDP_PRJ | ss3864022755 | Apr 26, 2020 (154) |
87 | KRGDB | ss3910778456 | Apr 26, 2020 (154) |
88 | KOGIC | ss3958602273 | Apr 26, 2020 (154) |
89 | EVA | ss3984448407 | Apr 26, 2021 (155) |
90 | EVA | ss3986337283 | Apr 26, 2021 (155) |
91 | TOPMED | ss4695324291 | Apr 26, 2021 (155) |
92 | TOMMO_GENOMICS | ss6062349828 | Nov 02, 2024 (157) |
93 | EVA | ss6234522859 | Nov 02, 2024 (157) |
94 | EVA | ss6297653894 | Nov 02, 2024 (157) |
95 | EVA | ss6322264015 | Nov 02, 2024 (157) |
96 | EVA | ss6330979717 | Nov 02, 2024 (157) |
97 | YEGNASUBRAMANIAN_LAB | ss6339393896 | Nov 02, 2024 (157) |
98 | EVA | ss6349657860 | Nov 02, 2024 (157) |
99 | KOGIC | ss6369522336 | Nov 02, 2024 (157) |
100 | GNOMAD | ss6426751066 | Nov 02, 2024 (157) |
101 | GNOMAD | ss6707992220 | Nov 02, 2024 (157) |
102 | TOMMO_GENOMICS | ss8176388425 | Nov 02, 2024 (157) |
103 | EVA | ss8237020161 | Nov 02, 2024 (157) |
104 | EVA | ss8237645242 | Nov 02, 2024 (157) |
105 | 1000G_HIGH_COVERAGE | ss8267581183 | Nov 02, 2024 (157) |
106 | TRAN_CS_UWATERLOO | ss8314415163 | Nov 02, 2024 (157) |
107 | EVA | ss8315126418 | Nov 02, 2024 (157) |
108 | EVA | ss8364130888 | Nov 02, 2024 (157) |
109 | HUGCELL_USP | ss8465357062 | Nov 02, 2024 (157) |
110 | EVA | ss8508363045 | Nov 02, 2024 (157) |
111 | EVA | ss8512473840 | Nov 02, 2024 (157) |
112 | EVA | ss8512473841 | Nov 02, 2024 (157) |
113 | 1000G_HIGH_COVERAGE | ss8553086965 | Nov 02, 2024 (157) |
114 | SANFORD_IMAGENETICS | ss8624616568 | Nov 02, 2024 (157) |
115 | SANFORD_IMAGENETICS | ss8639870340 | Nov 02, 2024 (157) |
116 | TOMMO_GENOMICS | ss8714119809 | Nov 02, 2024 (157) |
117 | EVA | ss8799402167 | Nov 02, 2024 (157) |
118 | YY_MCH | ss8807195553 | Nov 02, 2024 (157) |
119 | EVA | ss8841864405 | Nov 02, 2024 (157) |
120 | EVA | ss8847285223 | Nov 02, 2024 (157) |
121 | EVA | ss8848082766 | Nov 02, 2024 (157) |
122 | EVA | ss8848646340 | Nov 02, 2024 (157) |
123 | EVA | ss8855226419 | Nov 02, 2024 (157) |
124 | EVA | ss8882860664 | Nov 02, 2024 (157) |
125 | EVA | ss8968372676 | Nov 02, 2024 (157) |
126 | EVA | ss8979772107 | Nov 02, 2024 (157) |
127 | EVA | ss8981949158 | Nov 02, 2024 (157) |
128 | EVA | ss8982518780 | Nov 02, 2024 (157) |
129 | 1000Genomes | NC_000006.11 - 18130918 | Oct 12, 2018 (152) |
130 | 1000Genomes_30X | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
131 | The Avon Longitudinal Study of Parents and Children | NC_000006.11 - 18130918 | Oct 12, 2018 (152) |
132 | ExAC | NC_000006.11 - 18130918 | Oct 12, 2018 (152) |
133 | FINRISK | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
134 | The Danish reference pan genome | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
135 | gnomAD v4 - Exomes | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
136 | gnomAD v4 - Genomes | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
137 | Genome of the Netherlands Release 5 | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
138 | HapMap | NC_000006.12 - 18130687 | Apr 26, 2020 (154) |
139 | KOREAN population from KRGDB | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
140 | Korean Genome Project | NC_000006.12 - 18130687 | Apr 26, 2020 (154) |
141 | Korean Genome Project 4K | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
142 | Medical Genome Project healthy controls from Spanish population | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
143 | Northern Sweden | NC_000006.11 - 18130918 | Jul 13, 2019 (153) |
144 | MxGDAR/Encodat-PGx | NC_000006.11 - 18130918 | Apr 26, 2021 (155) |
145 | PharmGKB Aggregated | NC_000006.12 - 18130687 | Apr 26, 2020 (154) |
146 | Qatari | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
147 | SGDP_PRJ | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
148 | Siberian | NC_000006.11 - 18130918 | Apr 26, 2020 (154) |
149 | 38KJPN | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
150 | TopMed | NC_000006.12 - 18130687 | Apr 26, 2021 (155) |
151 | UK 10K study - Twins | NC_000006.11 - 18130918 | Oct 12, 2018 (152) |
152 | A Vietnamese Genetic Variation Database | NC_000006.11 - 18130918 | Jul 13, 2019 (153) |
153 | ALFA | NC_000006.12 - 18130687 | Nov 02, 2024 (157) |
154 | ClinVar | RCV000013559.35 | Nov 02, 2024 (157) |
155 | ClinVar | RCV000013562.32 | Nov 02, 2024 (157) |
156 | ClinVar | RCV000396233.15 | Nov 02, 2024 (157) |
History tab displays RefSNPs (Associated ID) from previous builds (Build) that now support the current RefSNP, and the dates, when the history was updated for each Associated ID (History Updated).
Associated ID | History Updated (Build) |
---|---|
rs1801205 | Apr 12, 2001 (94) |
rs16880254 | Mar 10, 2006 (126) |
rs29001646 | May 27, 2008 (130) |
rs52798150 | Sep 21, 2007 (128) |
rs61510596 | May 27, 2008 (130) |
Submission IDs | Observation SPDI | Canonical SPDI | Source RSIDs |
---|---|---|---|
ss6349657860, ss8512473841 | NC_000006.11:18130917:T:A | NC_000006.12:18130686:T:A | (self) |
ss491881231, ss825644720, ss1592188623, ss1712840126, ss3643551623 | NC_000006.10:18238896:T:C | NC_000006.12:18130686:T:C | (self) |
30923631, 17225114, 8192323, 40380, 7718228, 7641688, 17955850, 229044, 6534777, 1408, 7936331, 16039735, 4246370, 17225114, 3813147, ss240424863, ss342202115, ss479976551, ss490920222, ss491378155, ss534203861, ss652948628, ss780845863, ss783529410, ss974458968, ss982638248, ss1067475581, ss1073420853, ss1319172549, ss1581553289, ss1584043919, ss1615060464, ss1658054497, ss1688172336, ss1711113284, ss1752617943, ss1804304017, ss1917799662, ss1925894401, ss1946168662, ss1958867439, ss1966656270, ss2023565669, ss2094820454, ss2151730016, ss2634407225, ss2634407226, ss2707318195, ss2711061327, ss2735561433, ss2747554041, ss2836353081, ss2985984175, ss2998599174, ss3022579689, ss3029664475, ss3346859984, ss3629456166, ss3629456167, ss3635046782, ss3636761940, ss3640754078, ss3644901726, ss3646331127, ss3653088303, ss3733249912, ss3744546291, ss3745346868, ss3764676098, ss3772840657, ss3824158467, ss3825690598, ss3829760076, ss3864022755, ss3910778456, ss3984448407, ss3986337283, ss6234522859, ss6297653894, ss6322264015, ss6330979717, ss6339393896, ss8176388425, ss8315126418, ss8364130888, ss8508363045, ss8512473840, ss8512473841, ss8624616568, ss8639870340, ss8799402167, ss8841864405, ss8847285223, ss8848082766, ss8848646340, ss8968372676, ss8979772107, ss8981949158, ss8982518780 | NC_000006.11:18130917:T:C | NC_000006.12:18130686:T:C | (self) |
RCV000013559.35, RCV000013562.32, RCV000396233.15, 40612900, 22062013, 234761783, 3072622, 14980274, 19374234, 10621, 79725648, 532701849, 6559166236, ss244238585, ss275515909, ss3716687250, ss3726314857, ss3807838503, ss3958602273, ss4695324291, ss6062349828, ss6369522336, ss6426751066, ss6707992220, ss8237020161, ss8237645242, ss8267581183, ss8314415163, ss8465357062, ss8553086965, ss8714119809, ss8807195553, ss8855226419, ss8882860664 | NC_000006.12:18130686:T:C | NC_000006.12:18130686:T:C | (self) |
ss1554460, ss2421439, ss69368192, ss69370567, ss74811830, ss74822055, ss75279105, ss75287553, ss76875486, ss84164450, ss105439122, ss119383576, ss123105575, ss123336313, ss159977692, ss244272401 | NT_007592.15:18070917:T:C | NC_000006.12:18130686:T:C | (self) |
ss6349657860, ss8799402167 | NC_000006.11:18130917:T:G | NC_000006.12:18130686:T:G | (self) |
ss831883150 | NT_007592.15:18070917:T:G | NC_000006.12:18130686:T:G | (self) |
Publications tab displays PubMed articles citing the variation as a listing of PMID, Title, Author, Year, Journal, ordered by Year, descending.
PMID | Title | Author | Year | Journal |
---|---|---|---|---|
8561894 | Thiopurine methyltransferase pharmacogenetics: human gene cloning and characterization of a common polymorphism. | Szumlanski C et al. | 1996 | DNA and cell biology |
8644731 | Thiopurine S-methyltransferase deficiency: two nucleotide transitions define the most prevalent mutant allele associated with loss of catalytic activity in Caucasians. | Tai HL et al. | 1996 | American journal of human genetics |
9177237 | Enhanced proteolysis of thiopurine S-methyltransferase (TPMT) encoded by mutant alleles in humans (TPMT*3A, TPMT*2): mechanisms for the genetic polymorphism of TPMT activity. | Tai HL et al. | 1997 | Proceedings of the National Academy of Sciences of the United States of America |
9336428 | Azathioprine-induced severe pancytopenia due to a homozygous two-point mutation of the thiopurine methyltransferase gene in a patient with juvenile HLA-B27-associated spondylarthritis. | Leipold G et al. | 1997 | Arthritis and rheumatism |
9931345 | Thiopurine methyltransferase alleles in British and Ghanaian populations. | Ameyaw MM et al. | 1999 | Human molecular genetics |
9931346 | Polymorphism of the thiopurine S-methyltransferase gene in African-Americans. | Hon YY et al. | 1999 | Human molecular genetics |
10208641 | The frequency and distribution of thiopurine methyltransferase alleles in Caucasian and Asian populations. | Collie-Duguid ES et al. | 1999 | Pharmacogenetics |
10751626 | Genetic analysis of thiopurine methyltransferase polymorphism in a Japanese population. | Hiratsuka M et al. | 2000 | Mutation research |
15819814 | Severe azathioprine-induced myelotoxicity in a kidney transplant patient with thiopurine S-methyltransferase-deficient genotype (TPMT*3A/*3C). | Kurzawski M et al. | 2005 | Transplant international |
15967990 | Human thiopurine S-methyltransferase pharmacogenetics: variant allozyme misfolding and aggresome formation. | Wang L et al. | 2005 | Proceedings of the National Academy of Sciences of the United States of America |
16476125 | Molecular analysis of thiopurine S-methyltransferase alleles in Taiwan aborigines and Taiwanese. | Lu HF et al. | 2006 | Journal of clinical pharmacy and therapeutics |
18547414 | Genotyping panel for assessing response to cancer chemotherapy. | Dai Z et al. | 2008 | BMC medical genomics |
18662289 | Pharmacogenomic studies of the anticancer and immunosuppressive thiopurines mercaptopurine and azathioprine. | Hawwa AF et al. | 2008 | British journal of clinical pharmacology |
18685564 | Genetic polymorphism of inosine triphosphate pyrophosphatase is a determinant of mercaptopurine metabolism and toxicity during treatment for acute lymphoblastic leukemia. | Stocco G et al. | 2009 | Clinical pharmacology and therapeutics |
20855458 | Ecto-5'-nucleotidase and thiopurine cellular circulation: association with cytotoxicity. | Li F et al. | 2010 | Drug metabolism and disposition |
21395650 | Determinants of mercaptopurine toxicity in paediatric acute lymphoblastic leukemia maintenance therapy. | Adam de Beaumais T et al. | 2011 | British journal of clinical pharmacology |
22552919 | Bioinformatics and variability in drug response: a protein structural perspective. | Lahti JL et al. | 2012 | Journal of the Royal Society, Interface |
22871999 | Concordance of DMET plus genotyping results with those of orthogonal genotyping methods. | Fernandez CA et al. | 2012 | Clinical pharmacology and therapeutics |
22977575 | Accuracy of genotyping using the TaqMan PCR assay for single nucleotide polymorphisms responsible for thiopurine sensitivity in Japanese patients with inflammatory bowel disease. | Osaki R et al. | 2011 | Experimental and therapeutic medicine |
23133420 | Pharmacogenomic Diversity among Brazilians: Influence of Ancestry, Self-Reported Color, and Geographical Origin. | Suarez-Kurtz G et al. | 2012 | Frontiers in pharmacology |
23335936 | Multilocus genotypes of relevance for drug metabolizing enzymes and therapy with thiopurines in patients with acute lymphoblastic leukemia. | Stocco G et al. | 2012 | Frontiers in genetics |
23588304 | Replication of TPMT and ABCC3 genetic variants highly associated with cisplatin-induced hearing loss in children. | Pussegoda K et al. | 2013 | Clinical pharmacology and therapeutics |
24762746 | New genetic biomarkers predicting azathioprine blood concentrations in combination therapy with 5-aminosalicylic acid. | Uchiyama K et al. | 2014 | PloS one |
24774509 | Prevalence of TPMT and ITPA gene polymorphisms and effect on mercaptopurine dosage in Chilean children with acute lymphoblastic leukemia. | Farfan MJ et al. | 2014 | BMC cancer |
24787444 | An ontology-based, mobile-optimized system for pharmacogenomic decision support at the point-of-care. | Miñarro-Giménez JA et al. | 2014 | PloS one |
24795743 | Pharmacogenomics and adverse drug reactions in children. | Rieder MJ et al. | 2014 | Frontiers in genetics |
24860591 | Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes. | Almoguera B et al. | 2014 | Frontiers in genetics |
24944790 | Screening for 392 polymorphisms in 141 pharmacogenes. | Kim JY et al. | 2014 | Biomedical reports |
25266489 | Genetic polymorphisms of VIP variants in the Tajik ethnic group of northwest China. | Zhang J et al. | 2014 | BMC genetics |
25303517 | Association of ITPA genotype with event-free survival and relapse rates in children with acute lymphoblastic leukemia undergoing maintenance therapy. | Smid A et al. | 2014 | PloS one |
25419701 | Exploring the distribution of genetic markers of pharmacogenomics relevance in Brazilian and Mexican populations. | Bonifaz-Peña V et al. | 2014 | PloS one |
25551397 | Influence of genetic variants in TPMT and COMT associated with cisplatin induced hearing loss in patients with cancer: two new cohorts and a meta-analysis reveal significant heterogeneity between cohorts. | Hagleitner MM et al. | 2014 | PloS one |
25624441 | Inherited NUDT15 variant is a genetic determinant of mercaptopurine intolerance in children with acute lymphoblastic leukemia. | Yang JJ et al. | 2015 | Journal of clinical oncology |
25741362 | Use of pharmacogenomics in pediatric renal transplant recipients. | Medeiros M et al. | 2015 | Frontiers in genetics |
25887915 | Whole genome sequencing of an ethnic Pathan (Pakhtun) from the north-west of Pakistan. | Ilyas M et al. | 2015 | BMC genomics |
26091847 | Genetic polymorphisms of pharmacogenomic VIP variants in the Uygur population from northwestern China. | Wang L et al. | 2015 | BMC genetics |
26503813 | NUDT15 gene polymorphism related to mercaptopurine intolerance in Taiwan Chinese children with acute lymphoblastic leukemia. | Liang DC et al. | 2016 | The pharmacogenomics journal |
26785747 | Polymorphisms in genes involved in the absorption, distribution, metabolism, and excretion of drugs in the Kazakhs of Kazakhstan. | Iskakova AN et al. | 2016 | BMC genetics |
26858644 | Cross-Comparison of Exome Analysis, Next-Generation Sequencing of Amplicons, and the iPLEX(®) ADME PGx Panel for Pharmacogenomic Profiling. | Chua EW et al. | 2016 | Frontiers in pharmacology |
26878724 | NUDT15 polymorphisms alter thiopurine metabolism and hematopoietic toxicity. | Moriyama T et al. | 2016 | Nature genetics |
27233804 | Genetic polymorphisms of pharmacogenomic VIP variants in the Mongol of Northwestern China. | Jin T et al. | 2016 | BMC genetics |
27294413 | Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016. | Srivastava AK et al. | 2016 | Human genomics |
27307154 | A Simple Method for TPMT and ITPA Genotyping Using Multiplex HRMA for Patients Treated with Thiopurine Drugs. | Skrzypczak-Zielinska M et al. | 2016 | Molecular diagnosis & therapy |
27427275 | Association of germline genetic variants in RFC, IL15 and VDR genes with minimal residual disease in pediatric B-cell precursor ALL. | Dawidowska M et al. | 2016 | Scientific reports |
27446285 | Risk factors for symptomatic osteonecrosis in childhood ALL: A retrospective study of a Slovenian pediatric ALL population between 1970 and 2004. | Karas-Kuželički N et al. | 2016 | Experimental and therapeutic medicine |
27452984 | PACSIN2 polymorphism is associated with thiopurine-induced hematological toxicity in children with acute lymphoblastic leukaemia undergoing maintenance therapy. | Smid A et al. | 2016 | Scientific reports |
27564568 | Genomewide Approach Validates Thiopurine Methyltransferase Activity Is a Monogenic Pharmacogenomic Trait. | Liu C et al. | 2017 | Clinical pharmacology and therapeutics |
27618021 | Pharmacogenomics in Pediatric Oncology: Review of Gene-Drug Associations for Clinical Use. | Mlakar V et al. | 2016 | International journal of molecular sciences |
27636550 | A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics. | Mizzi C et al. | 2016 | PloS one |
28321040 | Whole exome sequencing detects variants of genes that mediate response to anticancer drugs. | Ohnami S et al. | 2017 | The Journal of toxicological sciences |
28445188 | TPMT, COMT and ACYP2 genetic variants in paediatric cancer patients with cisplatin-induced ototoxicity. | Thiesen S et al. | 2017 | Pharmacogenetics and genomics |
28462921 | One amino acid makes a difference-Characterization of a new TPMT allele and the influence of SAM on TPMT stability. | Iu YPH et al. | 2017 | Scientific reports |
28476189 | Analysis of Thiopurine S-Methyltransferase Deficient Alleles in Acute Lymphoblastic Leukemia Patients in Mexican Patients. | Jiménez-Morales S et al. | 2016 | Archives of medical research |
28498350 | Comparison of Direct Sequencing, Real-Time PCR-High Resolution Melt (PCR-HRM) and PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) Analysis for Genotyping of Common Thiopurine Intolerant Variant Alleles NUDT15 c.415C>T and TPMT c.719A>G (TPMT*3C). | Fong WY et al. | 2017 | Diagnostics (Basel, Switzerland) |
28771511 | Exploring public genomics data for population pharmacogenomics. | Lakiotaki K et al. | 2017 | PloS one |
29191122 | Association between TPMT*3C and decreased thiopurine S-methyltransferase activity in patients with neuromyelitis optica spectrum disorders in China. | Gong X et al. | 2018 | The International journal of neuroscience |
29193749 | Clinical Implementation of Pharmacogenetic Testing in a Hospital of the Spanish National Health System: Strategy and Experience Over 3 Years. | Borobia AM et al. | 2018 | Clinical and translational science |
29264794 | High frequency of mutant thiopurine S-methyltransferase genotypes in Mexican patients with systemic lupus erythematosus and rheumatoid arthritis. | Ramirez-Florencio M et al. | 2018 | Clinical rheumatology |
29373914 | Genetic Polymorphism of Thiopurine S-methyltransferase in Children with Acute Lymphoblastic Leukemia in Jordan. | Alsous M et al. | 2018 | Asian Pacific journal of cancer prevention |
29387964 | Role of TPMT and ITPA variants in mercaptopurine disposition. | Gerbek T et al. | 2018 | Cancer chemotherapy and pharmacology |
29681089 | Genetic variation in biotransformation enzymes, air pollution exposures, and risk of spina bifida. | Padula AM et al. | 2018 | American journal of medical genetics. Part A |
29720126 | Optimal predictor for 6-mercaptopurine intolerance in Chinese children with acute lymphoblastic leukemia: NUDT15, TPMT, or ITPA genetic variants? | Zhou H et al. | 2018 | BMC cancer |
30935835 | Development of duplex-crossed allele-specific PCR targeting of TPMT*3B and *3C using crossed allele-specific blockers to eliminate non-specific amplification. | Qu XM et al. | 2019 | Analytical biochemistry |
30987408 | Azathioprine Biotransformation in Young Patients with Inflammatory Bowel Disease: Contribution of Glutathione-S Transferase M1 and A1 Variants. | Lucafò M et al. | 2019 | Genes |
31019283 | Secondary actionable findings identified by exome sequencing: expected impact on the organisation of care from the study of 700 consecutive tests. | Thauvin-Robinet C et al. | 2019 | European journal of human genetics |
31024313 | NUDT15 Polymorphism Confer Increased Susceptibility to Thiopurine-Induced Leukopenia in Patients With Autoimmune Hepatitis and Related Cirrhosis. | Fan X et al. | 2019 | Frontiers in pharmacology |
31446180 | Genotype-based Treatment With Thiopurine Reduces Incidence of Myelosuppression in Patients With Inflammatory Bowel Diseases. | Chang JY et al. | 2020 | Clinical gastroenterology and hepatology |
31507415 | ITPA, TPMT, and NUDT15 Genetic Polymorphisms Predict 6-Mercaptopurine Toxicity in Middle Eastern Children With Acute Lymphoblastic Leukemia. | Moradveisi B et al. | 2019 | Frontiers in pharmacology |
31738745 | A meta-analysis of genome-wide association studies of epigenetic age acceleration. | Gibson J et al. | 2019 | PLoS genetics |
32213001 | UEG Week 2019 Poster Presentations. | 2019 | United European gastroenterology journal | |
32265697 | Screening of Novel Pharmacogenetic Candidates for Mercaptopurine-Induced Toxicity in Patients With Acute Lymphoblastic Leukemia. | Cao M et al. | 2020 | Frontiers in pharmacology |
32326111 | Role of Genetic Variations in the Hepatic Handling of Drugs. | Marin JJG et al. | 2020 | International journal of molecular sciences |
32368972 | Genetic Analysis of Pharmacogenomic VIP Variants of ABCB1, VDR and TPMT Genes in an Ethnically Isolated Population from the North Caucasus Living in Jordan. | Al-Eitan LN et al. | 2020 | Current drug metabolism |
32453263 | Pharmacogenomics of thiopurines: distribution of TPMT and NUDT15 polymorphisms in the Brazilian Amazon. | Ferreira GMA et al. | 2020 | Pharmacogenetics and genomics |
32704308 | Thiopurine S-methyltransferase genetic polymorphisms in adult patients with inflammatory bowel diseases in the Latvian population. | Zalizko P et al. | 2020 | Therapeutic advances in gastroenterology |
32713039 | Complete remission of refractory pemphigus vulgaris in a Chinese patient with mutated NUDT15 by combination of minimal doses of azathioprine and prednisone. | Zhou XL et al. | 2020 | Dermatologic therapy |
32992962 | Association between the TPMT*3C (rs1142345) Polymorphism and the Risk of Death in the Treatment of Acute Lymphoblastic Leukemia in Children from the Brazilian Amazon Region. | Cardoso de Carvalho D et al. | 2020 | Genes |
33110249 | Population impact of pharmacogenetic tests in admixed populations across the Americas. | Suarez-Kurtz G et al. | 2021 | The pharmacogenomics journal |
33346461 | [Analysis of carrying clinically significant allelic variants of TPMT and DPYD genes associated with the response to drug therapy in cancer practice among 9 ethnic groups of the Russian Federation]. | Mirzaev KB et al. | 2020 | Terapevticheskii arkhiv |
33348915 | PharmFrag: An Easy and Fast Multiplex Pharmacogenetics Assay to Simultaneously Analyze 9 Genetic Polymorphisms Involved in Response Variability of Anticancer Drugs. | Bouvet R et al. | 2020 | International journal of molecular sciences |
33430289 | Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans. | Han N et al. | 2021 | Journal of personalized medicine |
33519226 | Genetic Diversity of Drug-Related Genes in Native Americans of the Brazilian Amazon. | Fernandes MR et al. | 2021 | Pharmacogenomics and personalized medicine |
33569925 | Gene-environment interactions between air pollution and biotransformation enzymes and risk of birth defects. | Padula AM et al. | 2021 | Birth defects research |
33846471 | Association of genetic variants in TPMT, ITPA, and NUDT15 with azathioprine-induced myelosuppression in southwest china patients with autoimmune hepatitis. | Miao Q et al. | 2021 | Scientific reports |
34385834 | Individualized Drugs' Selection by Evaluation of Drug Properties, Pharmacogenomics and Clinical Parameters: Performance of a Bioinformatic Tool Compared to a Clinically Established Counselling Process. | Borro M et al. | 2021 | Pharmacogenomics and personalized medicine |
34412101 | Comprehensive characterization of pharmacogenetic variants in TPMT and NUDT15 in children with acute lymphoblastic leukemia. | Moriyama T et al. | 2022 | Pharmacogenetics and genomics |
34621706 | Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform. | Kim B et al. | 2021 | Translational and clinical pharmacology |
34629890 | NUDT15 c.415C>T Polymorphism Predicts 6-MP Induced Early Myelotoxicity in Patients with Acute Lymphoblastic Leukemia Undergoing Maintenance Therapy. | Pai AA et al. | 2021 | Pharmacogenomics and personalized medicine |
34660484 | Effects of TPMT, NUDT15, and ITPA Genetic Variants on 6-Mercaptopurine Toxicity for Pediatric Patients With Acute Lymphoblastic Leukemia in Yunnan of China. | Mao X et al. | 2021 | Frontiers in pediatrics |
35089958 | Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population. | Goljan E et al. | 2022 | PloS one |
35431360 | Susceptibility to thiopurine toxicity by TPMT and NUDT15 variants in Colombian children with acute lymphoblastic leukemia. | Correa-Jimenez O et al. | 2021 | Colombia medica (Cali, Colombia) |
36164570 | Prevalence of exposure to pharmacogenetic drugs by the Saudis treated at the health care centers of the Ministry of National Guard. | Alshabeeb MA et al. | 2022 | Saudi pharmaceutical journal |
The Flanks tab provides retrieving flanking sequences of a SNP on all molecules that have placements.
Genomic regions, transcripts, and products
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NCBI Graphical Sequence Viewer display of the genomic region, transcripts and protein products for the reported RefSNP (rs).
Use the zoom option to view the nucleotides around the RefSNP and find other neighboring RefSNPs.
Visit Sequence Viewer for help with navigating inside the display and modifying the selection of displayed data tracks.
NCBI Graphical Sequence Viewer display of the genomic region, transcripts and protein products for the reported RefSNP (rs).
Use the zoom option to view the nucleotides around the RefSNP and find other neighboring RefSNPs.
Visit Sequence Viewer for help with navigating inside the display and modifying the selection of displayed data tracks.