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.
rs708272
Current Build 156
Released September 21, 2022
- Organism
- Homo sapiens
- Position
-
chr16:56962376 (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
- G>A / G>C
- Variation Type
- SNV Single Nucleotide Variation
- Frequency
-
A=0.375655 (99432/264690, TOPMED)A=0.424326 (96025/226300, GnomAD_exome)A=0.425887 (72342/169862, ALFA) (+ 23 more)
- Clinical Significance
- Reported in ClinVar
- Gene : Consequence
- CETP : Intron Variant
- Publications
- 105 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 |
---|---|---|---|---|
Total | Global | 169956 | G=0.574154 | A=0.425846, C=0.000000 |
European | Sub | 144230 | G=0.564564 | A=0.435436, C=0.000000 |
African | Sub | 8914 | G=0.7388 | A=0.2612, C=0.0000 |
African Others | Sub | 310 | G=0.755 | A=0.245, C=0.000 |
African American | Sub | 8604 | G=0.7383 | A=0.2617, C=0.0000 |
Asian | Sub | 3480 | G=0.6204 | A=0.3796, C=0.0000 |
East Asian | Sub | 2810 | G=0.6139 | A=0.3861, C=0.0000 |
Other Asian | Sub | 670 | G=0.648 | A=0.352, C=0.000 |
Latin American 1 | Sub | 544 | G=0.583 | A=0.417, C=0.000 |
Latin American 2 | Sub | 1578 | G=0.5323 | A=0.4677, C=0.0000 |
South Asian | Sub | 5150 | G=0.5126 | A=0.4874, C=0.0000 |
Other | Sub | 6060 | G=0.5960 | A=0.4040, C=0.0000 |
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 |
---|---|---|---|---|---|
TopMed | Global | Study-wide | 264690 | G=0.624345 | A=0.375655 |
gnomAD - Exomes | Global | Study-wide | 226300 | G=0.575674 | A=0.424326 |
gnomAD - Exomes | European | Sub | 115810 | G=0.573267 | A=0.426733 |
gnomAD - Exomes | Asian | Sub | 47372 | G=0.56168 | A=0.43832 |
gnomAD - Exomes | American | Sub | 33748 | G=0.52394 | A=0.47606 |
gnomAD - Exomes | African | Sub | 13828 | G=0.73814 | A=0.26186 |
gnomAD - Exomes | Ashkenazi Jewish | Sub | 9750 | G=0.6217 | A=0.3783 |
gnomAD - Exomes | Other | Sub | 5792 | G=0.5742 | A=0.4258 |
Allele Frequency Aggregator | Total | Global | 169862 | G=0.574113 | A=0.425887, C=0.000000 |
Allele Frequency Aggregator | European | Sub | 144154 | G=0.564514 | A=0.435486, C=0.000000 |
Allele Frequency Aggregator | African | Sub | 8914 | G=0.7388 | A=0.2612, C=0.0000 |
Allele Frequency Aggregator | Other | Sub | 6042 | G=0.5960 | A=0.4040, C=0.0000 |
Allele Frequency Aggregator | South Asian | Sub | 5150 | G=0.5126 | A=0.4874, C=0.0000 |
Allele Frequency Aggregator | Asian | Sub | 3480 | G=0.6204 | A=0.3796, C=0.0000 |
Allele Frequency Aggregator | Latin American 2 | Sub | 1578 | G=0.5323 | A=0.4677, C=0.0000 |
Allele Frequency Aggregator | Latin American 1 | Sub | 544 | G=0.583 | A=0.417, C=0.000 |
gnomAD - Genomes | Global | Study-wide | 139736 | G=0.618931 | A=0.381069 |
gnomAD - Genomes | European | Sub | 75676 | G=0.56234 | A=0.43766 |
gnomAD - Genomes | African | Sub | 41870 | G=0.73449 | A=0.26551 |
gnomAD - Genomes | American | Sub | 13608 | G=0.58128 | A=0.41872 |
gnomAD - Genomes | Ashkenazi Jewish | Sub | 3324 | G=0.6161 | A=0.3839 |
gnomAD - Genomes | East Asian | Sub | 3110 | G=0.6148 | A=0.3852 |
gnomAD - Genomes | Other | Sub | 2148 | G=0.6089 | A=0.3911 |
ExAC | Global | Study-wide | 109162 | G=0.570831 | A=0.429169 |
ExAC | Europe | Sub | 66122 | G=0.57276 | A=0.42724 |
ExAC | Asian | Sub | 23626 | G=0.55088 | A=0.44912 |
ExAC | American | Sub | 10778 | G=0.49425 | A=0.50575 |
ExAC | African | Sub | 7834 | G=0.7227 | A=0.2773 |
ExAC | Other | Sub | 802 | G=0.545 | A=0.455 |
The PAGE Study | Global | Study-wide | 78700 | G=0.65287 | A=0.34713 |
The PAGE Study | AfricanAmerican | Sub | 32514 | G=0.73055 | A=0.26945 |
The PAGE Study | Mexican | Sub | 10810 | G=0.54339 | A=0.45661 |
The PAGE Study | Asian | Sub | 8318 | G=0.5951 | A=0.4049 |
The PAGE Study | PuertoRican | Sub | 7918 | G=0.6374 | A=0.3626 |
The PAGE Study | NativeHawaiian | Sub | 4534 | G=0.6460 | A=0.3540 |
The PAGE Study | Cuban | Sub | 4230 | G=0.6357 | A=0.3643 |
The PAGE Study | Dominican | Sub | 3828 | G=0.6630 | A=0.3370 |
The PAGE Study | CentralAmerican | Sub | 2450 | G=0.5612 | A=0.4388 |
The PAGE Study | SouthAmerican | Sub | 1982 | G=0.5308 | A=0.4692 |
The PAGE Study | NativeAmerican | Sub | 1260 | G=0.5667 | A=0.4333 |
The PAGE Study | SouthAsian | Sub | 856 | G=0.537 | A=0.463 |
14KJPN | JAPANESE | Study-wide | 28258 | G=0.59268 | A=0.40732 |
8.3KJPN | JAPANESE | Study-wide | 16760 | G=0.59809 | A=0.40191 |
1000Genomes_30x | Global | Study-wide | 6404 | G=0.6237 | A=0.3763 |
1000Genomes_30x | African | Sub | 1786 | G=0.7542 | A=0.2458 |
1000Genomes_30x | Europe | Sub | 1266 | G=0.5774 | A=0.4226 |
1000Genomes_30x | South Asian | Sub | 1202 | G=0.5474 | A=0.4526 |
1000Genomes_30x | East Asian | Sub | 1170 | G=0.6197 | A=0.3803 |
1000Genomes_30x | American | Sub | 980 | G=0.544 | A=0.456 |
GO Exome Sequencing Project | Global | Study-wide | 5734 | G=0.6247 | A=0.3753 |
GO Exome Sequencing Project | European American | Sub | 3982 | G=0.5856 | A=0.4144 |
GO Exome Sequencing Project | African American | Sub | 1752 | G=0.7135 | A=0.2865 |
1000Genomes | Global | Study-wide | 5008 | G=0.6224 | A=0.3776 |
1000Genomes | African | Sub | 1322 | G=0.7534 | A=0.2466 |
1000Genomes | East Asian | Sub | 1008 | G=0.6250 | A=0.3750 |
1000Genomes | Europe | Sub | 1006 | G=0.5746 | A=0.4254 |
1000Genomes | South Asian | Sub | 978 | G=0.552 | A=0.448 |
1000Genomes | American | Sub | 694 | G=0.537 | A=0.463 |
Genetic variation in the Estonian population | Estonian | Study-wide | 4480 | G=0.5321 | A=0.4679 |
The Avon Longitudinal Study of Parents and Children | PARENT AND CHILD COHORT | Study-wide | 3854 | G=0.5589 | A=0.4411 |
UK 10K study - Twins | TWIN COHORT | Study-wide | 3708 | G=0.5523 | A=0.4477 |
KOREAN population from KRGDB | KOREAN | Study-wide | 2930 | G=0.6181 | A=0.3819, C=0.0000 |
Korean Genome Project | KOREAN | Study-wide | 1832 | G=0.6255 | A=0.3745 |
Genome of the Netherlands Release 5 | Genome of the Netherlands | Study-wide | 998 | G=0.580 | A=0.420 |
CNV burdens in cranial meningiomas | Global | Study-wide | 790 | G=0.585 | A=0.415 |
CNV burdens in cranial meningiomas | CRM | Sub | 790 | G=0.585 | A=0.415 |
Northern Sweden | ACPOP | Study-wide | 600 | G=0.518 | A=0.482 |
Medical Genome Project healthy controls from Spanish population | Spanish controls | Study-wide | 534 | G=0.584 | A=0.416 |
SGDP_PRJ | Global | Study-wide | 362 | G=0.373 | A=0.627 |
FINRISK | Finnish from FINRISK project | Study-wide | 300 | G=0.577 | A=0.423 |
PharmGKB Aggregated | Global | Study-wide | 272 | G=0.691 | A=0.309 |
PharmGKB Aggregated | PA151937402 | Sub | 136 | G=0.691 | A=0.309 |
PharmGKB Aggregated | PA151937904 | Sub | 136 | G=0.691 | A=0.309 |
Qatari | Global | Study-wide | 216 | G=0.602 | A=0.398 |
The Danish reference pan genome | Danish | Study-wide | 40 | G=0.33 | A=0.68 |
Siberian | Global | Study-wide | 32 | G=0.28 | A=0.72 |
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 16 | NC_000016.10:g.56962376G>A |
GRCh38.p14 chr 16 | NC_000016.10:g.56962376G>C |
GRCh37.p13 chr 16 | NC_000016.9:g.56996288G>A |
GRCh37.p13 chr 16 | NC_000016.9:g.56996288G>C |
CETP RefSeqGene | NG_008952.1:g.5454G>A |
CETP RefSeqGene | NG_008952.1:g.5454G>C |
Molecule type | Change | Amino acid[Codon] | SO Term |
---|---|---|---|
CETP transcript variant 1 | NM_000078.3:c.118+279G>A | N/A | Intron Variant |
CETP transcript variant 2 |
NM_001286085.2:c.118+279G… NM_001286085.2:c.118+279G>A |
N/A | Intron Variant |
CETP transcript variant X1 |
XM_006721124.4:c.118+279G… XM_006721124.4:c.118+279G>A |
N/A | Intron 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 |
---|---|---|
RCV001637726.3 | not provided | Benign |
RCV002243347.1 | Coronary artery disorder | Benign |
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 | G= | A | C |
---|---|---|---|
GRCh38.p14 chr 16 | NC_000016.10:g.56962376= | NC_000016.10:g.56962376G>A | NC_000016.10:g.56962376G>C |
GRCh37.p13 chr 16 | NC_000016.9:g.56996288= | NC_000016.9:g.56996288G>A | NC_000016.9:g.56996288G>C |
CETP RefSeqGene | NG_008952.1:g.5454= | NG_008952.1:g.5454G>A | NG_008952.1:g.5454G>C |
CETP transcript variant 1 | NM_000078.2:c.118+279= | NM_000078.2:c.118+279G>A | NM_000078.2:c.118+279G>C |
CETP transcript variant 1 | NM_000078.3:c.118+279= | NM_000078.3:c.118+279G>A | NM_000078.3:c.118+279G>C |
CETP transcript variant 2 | NM_001286085.2:c.118+279= | NM_001286085.2:c.118+279G>A | NM_001286085.2:c.118+279G>C |
CETP transcript variant X1 | XM_005255776.1:c.118+279= | XM_005255776.1:c.118+279G>A | XM_005255776.1:c.118+279G>C |
CETP transcript variant X1 | XM_006721124.4:c.118+279= | XM_006721124.4:c.118+279G>A | XM_006721124.4:c.118+279G>C |
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 | KWOK | ss1279119 | Oct 04, 2000 (86) |
2 | KWOK | ss1279959 | Oct 04, 2000 (86) |
3 | HGBASE | ss2420913 | Nov 14, 2000 (89) |
4 | PARC | ss23143013 | Sep 20, 2004 (126) |
5 | PERLEGEN | ss24432792 | Sep 20, 2004 (123) |
6 | ABI | ss43958162 | Mar 10, 2006 (126) |
7 | PHARMGKB_PARC | ss84138904 | Dec 14, 2007 (130) |
8 | PHARMGKB_PARC | ss84138920 | Dec 14, 2007 (130) |
9 | HGSV | ss84329604 | Dec 14, 2007 (130) |
10 | HGSV | ss85612267 | Dec 14, 2007 (130) |
11 | 1000GENOMES | ss109350826 | Jan 24, 2009 (130) |
12 | 1000GENOMES | ss115142208 | Jan 25, 2009 (130) |
13 | ILLUMINA-UK | ss118265921 | Feb 14, 2009 (130) |
14 | ENSEMBL | ss132511534 | Dec 01, 2009 (131) |
15 | ILLUMINA | ss154402868 | Dec 01, 2009 (131) |
16 | GMI | ss157396441 | Dec 01, 2009 (131) |
17 | ILLUMINA | ss159578111 | Dec 01, 2009 (131) |
18 | COMPLETE_GENOMICS | ss168275926 | Jul 04, 2010 (132) |
19 | COMPLETE_GENOMICS | ss169831300 | Jul 04, 2010 (132) |
20 | COMPLETE_GENOMICS | ss171291741 | Jul 04, 2010 (132) |
21 | ILLUMINA | ss174233012 | Jul 04, 2010 (132) |
22 | BUSHMAN | ss201740909 | Jul 04, 2010 (132) |
23 | 1000GENOMES | ss227262004 | Jul 14, 2010 (132) |
24 | 1000GENOMES | ss237039588 | Jul 15, 2010 (132) |
25 | 1000GENOMES | ss243376550 | Jul 15, 2010 (132) |
26 | ILLUMINA | ss244307800 | Jul 04, 2010 (132) |
27 | BL | ss255729926 | May 09, 2011 (134) |
28 | GMI | ss282546413 | May 04, 2012 (137) |
29 | GMI | ss287081794 | Apr 25, 2013 (138) |
30 | ILLUMINA | ss479982690 | May 04, 2012 (137) |
31 | ILLUMINA | ss483521597 | May 04, 2012 (137) |
32 | CLINSEQ_SNP | ss491719210 | May 04, 2012 (137) |
33 | ILLUMINA | ss533445224 | Sep 08, 2015 (146) |
34 | TISHKOFF | ss564922131 | Apr 25, 2013 (138) |
35 | SSMP | ss660696146 | Apr 25, 2013 (138) |
36 | NHLBI-ESP | ss713307498 | Apr 25, 2013 (138) |
37 | ILLUMINA | ss779688466 | Sep 08, 2015 (146) |
38 | ILLUMINA | ss781117350 | Sep 08, 2015 (146) |
39 | ILLUMINA | ss833089173 | Aug 21, 2014 (142) |
40 | ILLUMINA | ss833680001 | Aug 21, 2014 (142) |
41 | ILLUMINA | ss835162304 | Sep 08, 2015 (146) |
42 | JMKIDD_LAB | ss974495089 | Aug 21, 2014 (142) |
43 | EVA-GONL | ss992526062 | Aug 21, 2014 (142) |
44 | JMKIDD_LAB | ss1067561883 | Aug 21, 2014 (142) |
45 | JMKIDD_LAB | ss1080650699 | Aug 21, 2014 (142) |
46 | 1000GENOMES | ss1356389502 | Aug 21, 2014 (142) |
47 | DDI | ss1427858468 | Apr 01, 2015 (144) |
48 | EVA_GENOME_DK | ss1577928655 | Apr 01, 2015 (144) |
49 | EVA_FINRISK | ss1584100143 | Apr 01, 2015 (144) |
50 | EVA_UK10K_ALSPAC | ss1634499395 | Apr 01, 2015 (144) |
51 | EVA_UK10K_TWINSUK | ss1677493428 | Apr 01, 2015 (144) |
52 | EVA_EXAC | ss1692313928 | Apr 01, 2015 (144) |
53 | EVA_DECODE | ss1696560594 | Apr 01, 2015 (144) |
54 | EVA_MGP | ss1711430501 | Apr 01, 2015 (144) |
55 | HAMMER_LAB | ss1808529320 | Sep 08, 2015 (146) |
56 | WEILL_CORNELL_DGM | ss1935962300 | Feb 12, 2016 (147) |
57 | ILLUMINA | ss1959681905 | Feb 12, 2016 (147) |
58 | GENOMED | ss1968270394 | Jul 19, 2016 (147) |
59 | JJLAB | ss2028764606 | Sep 14, 2016 (149) |
60 | USC_VALOUEV | ss2157201138 | Dec 20, 2016 (150) |
61 | HUMAN_LONGEVITY | ss2212446382 | Dec 20, 2016 (150) |
62 | SYSTEMSBIOZJU | ss2628873900 | Nov 08, 2017 (151) |
63 | ILLUMINA | ss2633322708 | Nov 08, 2017 (151) |
64 | GRF | ss2701725812 | Nov 08, 2017 (151) |
65 | ILLUMINA | ss2710834152 | Nov 08, 2017 (151) |
66 | GNOMAD | ss2742003168 | Nov 08, 2017 (151) |
67 | GNOMAD | ss2749548531 | Nov 08, 2017 (151) |
68 | GNOMAD | ss2943414425 | Nov 08, 2017 (151) |
69 | AFFY | ss2985069724 | Nov 08, 2017 (151) |
70 | AFFY | ss2985705869 | Nov 08, 2017 (151) |
71 | SWEGEN | ss3014571103 | Nov 08, 2017 (151) |
72 | ILLUMINA | ss3021709790 | Nov 08, 2017 (151) |
73 | BIOINF_KMB_FNS_UNIBA | ss3028200990 | Nov 08, 2017 (151) |
74 | CSHL | ss3351468585 | Nov 08, 2017 (151) |
75 | ILLUMINA | ss3627531742 | Oct 12, 2018 (152) |
76 | ILLUMINA | ss3631308870 | Oct 12, 2018 (152) |
77 | ILLUMINA | ss3638127224 | Oct 12, 2018 (152) |
78 | ILLUMINA | ss3641957293 | Oct 12, 2018 (152) |
79 | OMUKHERJEE_ADBS | ss3646494947 | Oct 12, 2018 (152) |
80 | URBANLAB | ss3650518070 | Oct 12, 2018 (152) |
81 | ILLUMINA | ss3652118773 | Oct 12, 2018 (152) |
82 | ILLUMINA | ss3653841685 | Oct 12, 2018 (152) |
83 | EGCUT_WGS | ss3681546683 | Jul 13, 2019 (153) |
84 | EVA_DECODE | ss3699333703 | Jul 13, 2019 (153) |
85 | ILLUMINA | ss3725565171 | Jul 13, 2019 (153) |
86 | ACPOP | ss3741542199 | Jul 13, 2019 (153) |
87 | EVA | ss3753982468 | Jul 13, 2019 (153) |
88 | PAGE_CC | ss3771881880 | Jul 13, 2019 (153) |
89 | PACBIO | ss3788049962 | Jul 13, 2019 (153) |
90 | PACBIO | ss3793031275 | Jul 13, 2019 (153) |
91 | PACBIO | ss3797916270 | Jul 13, 2019 (153) |
92 | KHV_HUMAN_GENOMES | ss3819269195 | Jul 13, 2019 (153) |
93 | EVA | ss3825018302 | Apr 27, 2020 (154) |
94 | EVA | ss3825879734 | Apr 27, 2020 (154) |
95 | EVA | ss3834588253 | Apr 27, 2020 (154) |
96 | EVA | ss3840899797 | Apr 27, 2020 (154) |
97 | EVA | ss3846391725 | Apr 27, 2020 (154) |
98 | SGDP_PRJ | ss3884512530 | Apr 27, 2020 (154) |
99 | KRGDB | ss3934004596 | Apr 27, 2020 (154) |
100 | KOGIC | ss3977657485 | Apr 27, 2020 (154) |
101 | FSA-LAB | ss3984094413 | Apr 27, 2021 (155) |
102 | EVA | ss3984713496 | Apr 27, 2021 (155) |
103 | EVA | ss3986688383 | Apr 27, 2021 (155) |
104 | EVA | ss4017737944 | Apr 27, 2021 (155) |
105 | TOPMED | ss5016620462 | Apr 27, 2021 (155) |
106 | TOMMO_GENOMICS | ss5219733139 | Apr 27, 2021 (155) |
107 | EVA | ss5236933738 | Apr 27, 2021 (155) |
108 | 1000G_HIGH_COVERAGE | ss5301083701 | Oct 16, 2022 (156) |
109 | EVA | ss5315840765 | Oct 16, 2022 (156) |
110 | EVA | ss5423942773 | Oct 16, 2022 (156) |
111 | HUGCELL_USP | ss5494424212 | Oct 16, 2022 (156) |
112 | 1000G_HIGH_COVERAGE | ss5603796494 | Oct 16, 2022 (156) |
113 | EVA | ss5624062810 | Oct 16, 2022 (156) |
114 | SANFORD_IMAGENETICS | ss5624381067 | Oct 16, 2022 (156) |
115 | SANFORD_IMAGENETICS | ss5658975018 | Oct 16, 2022 (156) |
116 | TOMMO_GENOMICS | ss5774788682 | Oct 16, 2022 (156) |
117 | EVA | ss5799456523 | Oct 16, 2022 (156) |
118 | YY_MCH | ss5816004768 | Oct 16, 2022 (156) |
119 | EVA | ss5846458325 | Oct 16, 2022 (156) |
120 | EVA | ss5847463189 | Oct 16, 2022 (156) |
121 | EVA | ss5847772178 | Oct 16, 2022 (156) |
122 | EVA | ss5848426006 | Oct 16, 2022 (156) |
123 | EVA | ss5851581601 | Oct 16, 2022 (156) |
124 | EVA | ss5899244212 | Oct 16, 2022 (156) |
125 | EVA | ss5936563938 | Oct 16, 2022 (156) |
126 | EVA | ss5950369459 | Oct 16, 2022 (156) |
127 | EVA | ss5979486501 | Oct 16, 2022 (156) |
128 | EVA | ss5981295567 | Oct 16, 2022 (156) |
129 | 1000Genomes | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
130 | 1000Genomes_30x | NC_000016.10 - 56962376 | Oct 16, 2022 (156) |
131 | The Avon Longitudinal Study of Parents and Children | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
132 | Genetic variation in the Estonian population | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
133 | ExAC | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
134 | FINRISK | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
135 | The Danish reference pan genome | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
136 | gnomAD - Genomes | NC_000016.10 - 56962376 | Apr 27, 2021 (155) |
137 | gnomAD - Exomes | NC_000016.9 - 56996288 | Jul 13, 2019 (153) |
138 | GO Exome Sequencing Project | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
139 | Genome of the Netherlands Release 5 | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
140 | KOREAN population from KRGDB | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
141 | Korean Genome Project | NC_000016.10 - 56962376 | Apr 27, 2020 (154) |
142 | Medical Genome Project healthy controls from Spanish population | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
143 | Northern Sweden | NC_000016.9 - 56996288 | Jul 13, 2019 (153) |
144 | The PAGE Study | NC_000016.10 - 56962376 | Jul 13, 2019 (153) |
145 | CNV burdens in cranial meningiomas | NC_000016.9 - 56996288 | Apr 27, 2021 (155) |
146 | PharmGKB Aggregated | NC_000016.10 - 56962376 | Apr 27, 2020 (154) |
147 | Qatari | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
148 | SGDP_PRJ | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
149 | Siberian | NC_000016.9 - 56996288 | Apr 27, 2020 (154) |
150 | 8.3KJPN | NC_000016.9 - 56996288 | Apr 27, 2021 (155) |
151 | 14KJPN | NC_000016.10 - 56962376 | Oct 16, 2022 (156) |
152 | TopMed | NC_000016.10 - 56962376 | Apr 27, 2021 (155) |
153 | UK 10K study - Twins | NC_000016.9 - 56996288 | Oct 12, 2018 (152) |
154 | ALFA | NC_000016.10 - 56962376 | Apr 27, 2021 (155) |
155 | ClinVar | RCV001637726.3 | Oct 16, 2022 (156) |
156 | ClinVar | RCV002243347.1 | Oct 16, 2022 (156) |
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) |
---|---|
rs17237904 | Mar 10, 2006 (126) |
rs17290342 | Oct 08, 2004 (123) |
rs57207652 | May 23, 2008 (130) |
Submission IDs | Observation SPDI | Canonical SPDI | Source RSIDs |
---|---|---|---|
ss84329604, ss85612267, ss109350826, ss115142208, ss118265921, ss168275926, ss169831300, ss171291741, ss201740909, ss255729926, ss282546413, ss287081794, ss483521597, ss491719210, ss1696560594 | NC_000016.8:55553788:G:A | NC_000016.10:56962375:G:A | (self) |
69556535, 38582836, 27284931, 2722520, 96604, 4140571, 11283305, 1475466, 17205374, 41181990, 546261, 14827064, 263033, 18004222, 36529510, 9717492, 77702446, 38582836, ss227262004, ss237039588, ss243376550, ss479982690, ss533445224, ss564922131, ss660696146, ss713307498, ss779688466, ss781117350, ss833089173, ss833680001, ss835162304, ss974495089, ss992526062, ss1067561883, ss1080650699, ss1356389502, ss1427858468, ss1577928655, ss1584100143, ss1634499395, ss1677493428, ss1692313928, ss1711430501, ss1808529320, ss1935962300, ss1959681905, ss1968270394, ss2028764606, ss2157201138, ss2628873900, ss2633322708, ss2701725812, ss2710834152, ss2742003168, ss2749548531, ss2943414425, ss2985069724, ss2985705869, ss3014571103, ss3021709790, ss3351468585, ss3627531742, ss3631308870, ss3638127224, ss3641957293, ss3646494947, ss3652118773, ss3653841685, ss3681546683, ss3741542199, ss3753982468, ss3788049962, ss3793031275, ss3797916270, ss3825018302, ss3825879734, ss3834588253, ss3840899797, ss3884512530, ss3934004596, ss3984094413, ss3984713496, ss3986688383, ss4017737944, ss5219733139, ss5315840765, ss5423942773, ss5624062810, ss5624381067, ss5658975018, ss5799456523, ss5846458325, ss5847463189, ss5847772178, ss5848426006, ss5936563938, ss5950369459, ss5979486501, ss5981295567 | NC_000016.9:56996287:G:A | NC_000016.10:56962375:G:A | (self) |
RCV001637726.3, RCV002243347.1, 91322429, 490599066, 34035486, 1103349, 4379, 108625786, 232166123, 8864982890, ss2212446382, ss3028200990, ss3650518070, ss3699333703, ss3725565171, ss3771881880, ss3819269195, ss3846391725, ss3977657485, ss5016620462, ss5236933738, ss5301083701, ss5494424212, ss5603796494, ss5774788682, ss5816004768, ss5851581601, ss5899244212 | NC_000016.10:56962375:G:A | NC_000016.10:56962375:G:A | (self) |
ss1279119, ss1279959, ss2420913, ss23143013, ss24432792, ss43958162, ss84138904, ss84138920, ss132511534, ss154402868, ss157396441, ss159578111, ss174233012, ss244307800 | NT_010498.15:10610486:G:A | NC_000016.10:56962375:G:A | (self) |
41181990, ss3934004596 | NC_000016.9:56996287:G:C | NC_000016.10:56962375:G:C | (self) |
8864982890 | NC_000016.10:56962375:G:C | NC_000016.10:56962375:G:C | (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 |
---|---|---|---|---|
12475937 | Association testing by DNA pooling: an effective initial screen. | Bansal A et al. | 2002 | Proceedings of the National Academy of Sciences of the United States of America |
17157861 | Associations between HDL-cholesterol and polymorphisms in hepatic lipase and lipoprotein lipase genes are modified by dietary fat intake in African American and White adults. | Nettleton JA et al. | 2007 | Atherosclerosis |
18164013 | High HDL cholesterol does not protect against coronary artery disease when associated with combined cholesteryl ester transfer protein and hepatic lipase gene variants. | van Acker BA et al. | 2008 | Atherosclerosis |
18275964 | Low-density lipoprotein and high-density lipoprotein cholesterol levels in relation to genetic polymorphisms and menopausal status: the Atherosclerosis Risk in Communities (ARIC) Study. | Chamberlain AM et al. | 2008 | Atherosclerosis |
18518852 | Common variation in the CETP gene and the implications for cardiovascular disease and its treatment: an updated analysis. | Dullaart RP et al. | 2008 | Pharmacogenomics |
18549840 | Cholesterol ester transfer protein, interleukin-8, peroxisome proliferator activator receptor alpha, and Toll-like receptor 4 genetic variations and risk of incident nonfatal myocardial infarction and ischemic stroke. | Enquobahrie DA et al. | 2008 | The American journal of cardiology |
18560005 | Association of cholesteryl ester transfer protein genotypes with CETP mass and activity, lipid levels, and coronary risk. | Thompson A et al. | 2008 | JAMA |
18637884 | Cholesteryl ester transfer protein (CETP) genetic variation and early onset of non-fatal myocardial infarction. | Meiner V et al. | 2008 | Annals of human genetics |
18835593 | Interactions between alcohol intake and the polymorphism of rs708272 on serum high-density lipoprotein cholesterol levels in the Guangxi Hei Yi Zhuang population. | Zhou Y et al. | 2008 | Alcohol (Fayetteville, N.Y.) |
19041386 | Genetic-epidemiological evidence on genes associated with HDL cholesterol levels: a systematic in-depth review. | Boes E et al. | 2009 | Experimental gerontology |
19263529 | Genetic risk factors in recurrent venous thromboembolism: A multilocus, population-based, prospective approach. | Zee RY et al. | 2009 | Clinica chimica acta; international journal of clinical chemistry |
19336475 | Integrated associations of genotypes with multiple blood biomarkers linked to coronary heart disease risk. | Drenos F et al. | 2009 | Human molecular genetics |
19364639 | The effect of a novel intergenic polymorphism (rs11774572) on HDL-cholesterol concentrations depends on TaqIB polymorphism in the cholesterol ester transfer protein gene. | Junyent M et al. | 2010 | Nutrition, metabolism, and cardiovascular diseases |
19379518 | Development of a fingerprinting panel using medically relevant polymorphisms. | Cross DS et al. | 2009 | BMC medical genomics |
19913121 | Gene-centric association signals for lipids and apolipoproteins identified via the HumanCVD BeadChip. | Talmud PJ et al. | 2009 | American journal of human genetics |
20031564 | Polymorphism in the CETP gene region, HDL cholesterol, and risk of future myocardial infarction: Genomewide analysis among 18 245 initially healthy women from the Women's Genome Health Study. | Ridker PM et al. | 2009 | Circulation. Cardiovascular genetics |
20082485 | Genetic variants involved in gallstone formation and capsaicin metabolism, and the risk of gallbladder cancer in Chilean women. | Báez S et al. | 2010 | World journal of gastroenterology |
20205905 | Association of repeatedly measured intermediate risk factors for complex diseases with high dimensional SNP data. | Waaijenborg S et al. | 2010 | Algorithms for molecular biology |
20421590 | Genetic causes of high and low serum HDL-cholesterol. | Weissglas-Volkov D et al. | 2010 | Journal of lipid research |
20489166 | Cholesteryl ester transfer protein polymorphism (TaqIB) associates with risk in postinfarction patients with high C-reactive protein and high-density lipoprotein cholesterol levels. | Corsetti JP et al. | 2010 | Arteriosclerosis, thrombosis, and vascular biology |
20565774 | Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project. | Cross DS et al. | 2010 | BMC genetics |
21056700 | Lack of replication in polymorphisms reported to be associated with atrial fibrillation. | Sinner MF et al. | 2011 | Heart rhythm |
21146168 | LPL polymorphism (D9N) predicts cardiovascular disease risk directly and through interaction with CETP polymorphism (TaqIB) in women with high HDL cholesterol and CRP. | Corsetti JP et al. | 2011 | Atherosclerosis |
21288825 | Association of pharmacogenetic markers with premature discontinuation of first-line anti-HIV therapy: an observational cohort study. | Lubomirov R et al. | 2011 | The Journal of infectious diseases |
21316679 | Associations between common genetic polymorphisms in the liver X receptor alpha and its target genes with the serum HDL-cholesterol concentration in adolescents of the HELENA Study. | Legry V et al. | 2011 | Atherosclerosis |
21423763 | Interactions of the apolipoprotein A5 gene polymorphisms and alcohol consumption on serum lipid levels. | Yin RX et al. | 2011 | PloS one |
21467728 | Profile of participants and genotype distributions of 108 polymorphisms in a cross-sectional study of associations of genotypes with lifestyle and clinical factors: a project in the Japan Multi-Institutional Collaborative Cohort (J-MICC) Study. | Wakai K et al. | 2011 | Journal of epidemiology |
21708280 | Candidate gene studies in gallbladder cancer: a systematic review and meta-analysis. | Srivastava K et al. | 2011 | Mutation research |
21860704 | Implications of discoveries from genome-wide association studies in current cardiovascular practice. | Jeemon P et al. | 2011 | World journal of cardiology |
21894447 | Are centenarians genetically predisposed to lower disease risk? | Ruiz JR et al. | 2012 | Age (Dordrecht, Netherlands) |
22024213 | A novel gene-environment interaction involved in endometriosis. | McCarty CA et al. | 2012 | International journal of gynaecology and obstetrics |
22073289 | Interaction between cholesteryl ester transfer protein and hepatic lipase encoding genes and the risk of type 2 diabetes: results from the Telde study. | López-Ríos L et al. | 2011 | PloS one |
22122979 | The CETP I405V polymorphism is associated with an increased risk of Alzheimer's disease. | Yu L et al. | 2012 | Aging cell |
22143414 | Genetic variation in cholesterol ester transfer protein, serum CETP activity, and coronary artery disease risk in Asian Indian diabetic cohort. | Schierer A et al. | 2012 | Pharmacogenetics and genomics |
22229114 | Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids. | Carlquist JF et al. | 2011 | Journal of clinical & experimental cardiology |
22328972 | A Database of Gene-Environment Interactions Pertaining to Blood Lipid Traits, Cardiovascular Disease and Type 2 Diabetes. | Lee YC et al. | 2011 | Journal of data mining in genomics & proteomics |
22403620 | Cholesteryl Ester Transfer Protein (CETP) polymorphisms affect mRNA splicing, HDL levels, and sex-dependent cardiovascular risk. | Papp AC et al. | 2012 | PloS one |
22715478 | Genotypes associated with lipid metabolism contribute to differences in serum lipid profile of GH-deficient adults before and after GH replacement therapy. | Barbosa EJ et al. | 2012 | European journal of endocrinology |
23039238 | Several genetic polymorphisms interact with overweight/obesity to influence serum lipid levels. | Yin RX et al. | 2012 | Cardiovascular diabetology |
23389097 | The frequency of 4 common gene polymorphisms in nonagenarians, centenarians, and average life span individuals. | Kolovou G et al. | 2014 | Angiology |
23497168 | Omega-3 fatty acids, polymorphisms and lipid related cardiovascular disease risk factors in the Inuit population. | Rudkowska I et al. | 2013 | Nutrition & metabolism |
23533563 | Novel risk factors for premature peripheral arterial occlusive disease in non-diabetic patients: a case-control study. | Bérard AM et al. | 2013 | PloS one |
23656756 | Single nucleotide polymorphisms in CETP, SLC46A1, SLC19A1, CD36, BCMO1, APOA5, and ABCA1 are significant predictors of plasma HDL in healthy adults. | Clifford AJ et al. | 2013 | Lipids in health and disease |
23675527 | The association of common SNPs and haplotypes in CETP gene with HDL cholesterol levels in Latvian population. | Radovica I et al. | 2013 | PloS one |
23891427 | Single nucleotide polymorphisms in cholesteryl ester transfer protein gene and recurrent coronary heart disease or mortality in patients with established atherosclerosis. | Virani SS et al. | 2013 | The American journal of cardiology |
23988150 | Multi-locus candidate gene analyses of lipid levels in a pediatric Turkish cohort: lessons learned on LPL, CETP, LIPC, ABCA1, and SHBG. | Agirbasli M et al. | 2013 | Omics |
24319689 | The roles of genetic polymorphisms and human immunodeficiency virus infection in lipid metabolism. | de Almeida ER et al. | 2013 | BioMed research international |
24346170 | Genetic evidence for role of carotenoids in age-related macular degeneration in the Carotenoids in Age-Related Eye Disease Study (CAREDS). | Meyers KJ et al. | 2014 | Investigative ophthalmology & visual science |
24944790 | Screening for 392 polymorphisms in 141 pharmacogenes. | Kim JY et al. | 2014 | Biomedical reports |
25073458 | CETP gene polymorphism in the caucasian population of West Siberia and in groups contrast by total serum cholesterol levels. | Shakhtshneider EV et al. | 2014 | Bulletin of experimental biology and medicine |
25105518 | Relationships between CETP genetic polymorphisms and Alzheimer's disease risk: a meta-analysis. | Chen JJ et al. | 2014 | DNA and cell biology |
25224634 | Genetic variation in key genes associated with statin therapy in the Azores Islands (Portugal) healthy population. | Melo MS et al. | 2015 | Annals of human biology |
25561046 | Circulating cholesteryl ester transfer protein and coronary heart disease: mendelian randomization meta-analysis. | Niu W et al. | 2015 | Circulation. Cardiovascular genetics |
25671407 | A systems genetics approach to dyslipidemia in children and adolescents. | White MJ et al. | 2015 | Omics |
25864161 | Ethnic differences in the association between lipid metabolism genes and lipid levels in black and white South African women. | Ellman N et al. | 2015 | Atherosclerosis |
25951190 | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology. | Drenos F et al. | 2015 | PloS one |
26101956 | Polymorphisms in LPL, CETP, and HL protect HIV-infected patients from atherogenic dyslipidemia in an allele-dose-dependent manner. | Guardiola M et al. | 2015 | AIDS research and human retroviruses |
26365620 | Genetic association of APOA5 and APOE with metabolic syndrome and their interaction with health-related behavior in Korean men. | Son KY et al. | 2015 | Lipids in health and disease |
26370976 | Polymorphisms in the LPL and CETP Genes and Haplotype in the ESR1 Gene Are Associated with Metabolic Syndrome in Women from Southwestern Mexico. | Cahua-Pablo JÁ et al. | 2015 | International journal of molecular sciences |
26694435 | Association between Eight Functional Polymorphisms and Haplotypes in the Cholesterol Ester Transfer Protein (CETP) Gene and Dyslipidemia in National Minority Adults in the Far West Region of China. | Guo S et al. | 2015 | International journal of environmental research and public health |
26936456 | The impact of common polymorphisms in CETP and ABCA1 genes with the risk of coronary artery disease in Saudi Arabians. | Cyrus C et al. | 2016 | Human genomics |
26971241 | Influence of Genetic Risk Factors on Coronary Heart Disease Occurrence in Afro-Caribbeans. | Larifla L et al. | 2016 | The Canadian journal of cardiology |
27415775 | Gene Polymorphisms Affect the Effectiveness of Atorvastatin in Treating Ischemic Stroke Patients. | Yue YH et al. | 2016 | Cellular physiology and biochemistry |
27496123 | Taq1B Polymorphism of Cholesteryl Ester Transfer Protein (CETP) and Its Effects on the Serum Lipid Levels in Metabolic Syndrome Patients. | Maroufi NF et al. | 2016 | Biochemical genetics |
27545125 | [Association between CETP polymorphisms and haplotypes with dyslipidemia in Xinjiang Uygur and Kazak residents]. | Hu YH et al. | 2016 | Zhonghua xin xue guan bing za zhi |
27684940 | Gene Polymorphisms of FABP2, ADIPOQ and ANP and Risk of Hypertriglyceridemia and Metabolic Syndrome in Afro-Caribbeans. | Larifla L et al. | 2016 | PloS one |
27716211 | A 19-SNP coronary heart disease gene score profile in subjects with type 2 diabetes: the coronary heart disease risk in type 2 diabetes (CoRDia study) study baseline characteristics. | Beaney KE et al. | 2016 | Cardiovascular diabetology |
27717122 | Genetic variants in CETP increase risk of intracerebral hemorrhage. | Anderson CD et al. | 2016 | Annals of neurology |
27757045 | Pharmacogenomics of statins: understanding susceptibility to adverse effects. | Kitzmiller JP et al. | 2016 | Pharmacogenomics and personalized medicine |
27827461 | Association and interaction of APOA5, BUD13, CETP, LIPA and health-related behavior with metabolic syndrome in a Taiwanese population. | Lin E et al. | 2016 | Scientific reports |
27900488 | Additive Antiatherogenic Effects of CETP rs708272 on Serum LDL Subfraction Levels in Patients with CHD Under Statin Therapy. | Kanca D et al. | 2017 | Biochemical genetics |
28143480 | Common variants in the genes of triglyceride and HDL-C metabolism lack association with coronary artery disease in the Pakistani subjects. | Shahid SU et al. | 2017 | Lipids in health and disease |
28167353 | Genetic risk analysis of coronary artery disease in Pakistani subjects using a genetic risk score of 21 variants. | Shahid SU et al. | 2017 | Atherosclerosis |
28290785 | [Genetic Risk Factors of Macrovascular Complications in Patients With Type 2 Diabetes]. | Bystrova AA et al. | 2017 | Kardiologiia |
28315561 | Polymorphisms of lipid metabolism enzyme-coding genes in patients with diabetic dyslipidemia. | Tetik Vardarlı A et al. | 2017 | Anatolian journal of cardiology |
28623937 | The association of lipid metabolism relative gene polymorphisms and ischemic stroke in Han and Uighur population of Xinjiang. | Yue YH et al. | 2017 | Lipids in health and disease |
28629169 | Association between Six CETP Polymorphisms and Metabolic Syndrome in Uyghur Adults from Xinjiang, China. | Hou H et al. | 2017 | International journal of environmental research and public health |
28652652 | Gallbladder cancer epidemiology, pathogenesis and molecular genetics: Recent update. | Sharma A et al. | 2017 | World journal of gastroenterology |
28918250 | Associations of cholesteryl ester transfer protein (CETP) gene variants with predisposition to age-related macular degeneration. | Liutkeviciene R et al. | 2017 | Gene |
29234452 | Genetic variations of cholesteryl ester transfer protein and diet interactions in relation to lipid profiles and coronary heart disease: a systematic review. | Mirmiran P et al. | 2017 | Nutrition & metabolism |
29570220 | CETP and LCAT Gene Polymorphisms Are Associated with High-Density Lipoprotein Subclasses and Acute Coronary Syndrome. | Vargas-Alarcon G et al. | 2018 | Lipids |
29973202 | Interaction between endothelial nitric oxide synthase rs1799983, cholesteryl ester-transfer protein rs708272 and angiopoietin-like protein 8 rs2278426 gene variants highly elevates the risk of type 2 diabetes mellitus and cardiovascular disease. | El-Lebedy D et al. | 2018 | Cardiovascular diabetology |
30026888 | Prediction of dyslipidemia using gene mutations, family history of diseases and anthropometric indicators in children and adolescents: The CASPIAN-III study. | Marateb HR et al. | 2018 | Computational and structural biotechnology journal |
30178218 | Relationship between CETP gene polymorphisms with coronary artery disease in Polish population. | Iwanicka J et al. | 2018 | Molecular biology reports |
30468910 | Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations. | Pikó P et al. | 2019 | Gene |
30544452 | Gender specific effect of CETP rs708272 polymorphism on lipid and atherogenic index of plasma levels but not on the risk of coronary artery disease: A case-control study. | Cai G et al. | 2018 | Medicine |
30584432 | Genetic Identification for Non-Communicable Disease: Findings from 20 Years of the Tehran Lipid and Glucose Study. | Daneshpour MS et al. | 2018 | International journal of endocrinology and metabolism |
30805016 | Logic Regression Analysis of Gene Polymorphisms and HDL Levels in a Nationally Representative Sample of Iranian Adolescents: The CASPIAN-III Study. | Moghadasi M et al. | 2017 | International journal of endocrinology and metabolism |
31012439 | Associations of cholesteryl ester transfer protein (CETP) gene variants with pituitary adenoma. | Sidaraite A et al. | 2020 | Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia |
31199170 | Does CETP rs5882, rs708272, SIRT1 rs12778366, FGFR2 rs2981582, STAT3 rs744166, VEGFA rs833068, IL6 rs1800795 polymorphisms play a role in optic neuritis development? | Gedvilaite G et al. | 2019 | Ophthalmic genetics |
31585025 | The influence of gene polymorphisms on postprandial triglyceride response after oral fat tolerance test meal in patients with diabetes mellitus. | Gavra P et al. | 2019 | International journal of clinical practice |
31739638 | Association of RS708272 (CETP Gene Variant) with Lipid Profile Parameters and the Risk of Myocardial Infarction in the White Population of Western Siberia. | Semaev S et al. | 2019 | Biomolecules |
31806882 | Genetic contribution to lipid target achievement with statin therapy: a prospective study. | Ruiz-Iruela C et al. | 2020 | The pharmacogenomics journal |
31910446 | Genome-wide association study of metabolic syndrome in Korean populations. | Oh SW et al. | 2020 | PloS one |
32346024 | Common genetic variation in obesity, lipid transfer genes and risk of Metabolic Syndrome: Results from IDEFICS/I.Family study and meta-analysis. | Nagrani R et al. | 2020 | Scientific reports |
32398726 | Genetic Polymorphisms, Mediterranean Diet and Microbiota-Associated Urolithin Metabotypes can Predict Obesity in Childhood-Adolescence. | Cortés-Martín A et al. | 2020 | Scientific reports |
32647408 | Association of Common Single Nucleotide Polymorphisms of Candidate Genes with Gallstone Disease: A Meta-Analysis. | Chauhan T et al. | 2020 | Indian journal of clinical biochemistry |
32666702 | Association of genetic variants at CETP, AGER, and CYP4F2 locus with the risk of atrophic age-related macular degeneration. | Liutkeviciene R et al. | 2020 | Molecular genetics & genomic medicine |
32682401 | Association of ESR1 (rs2234693 and rs9340799), CETP (rs708272), MTHFR (rs1801133 and rs2274976) and MS (rs185087) polymorphisms with Coronary Artery Disease (CAD). | Raina JK et al. | 2020 | BMC cardiovascular disorders |
33447072 | Association of CETP Gene Variants with Atherogenic Dyslipidemia Among Thai Patients Treated with Statin. | Srisawasdi P et al. | 2021 | Pharmacogenomics and personalized medicine |
34594055 | The rs4783961 and rs708272 genetic variants of the CETP gene are associated with coronary artery disease, but not with restenosis after coronary stenting. | Vargas-Alarcón G et al. | 2022 | Archivos de cardiologia de Mexico |
35098451 | A Nutrigenetic Update on CETP Gene-Diet Interactions on Lipid-Related Outcomes. | Wuni R et al. | 2022 | Current atherosclerosis reports |
35311709 | Pharmacogenetic Analyses of Therapeutic Effects of Lipophilic Statins on Cognitive and Functional Changes in Alzheimer's Disease. | de Oliveira FF et al. | 2022 | Journal of Alzheimer's disease |
35387194 | Personalized Dietary Recommendations Based on Lipid-Related Genetic Variants: A Systematic Review. | Pérez-Beltrán YE et al. | 2022 | Frontiers in nutrition |
36068255 | The effect of the association between CETP variant type and alcohol consumption on cholesterol level differs according to the ALDH2 variant type. | Yoo MG et al. | 2022 | Scientific reports |
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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Help
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.