rs218264
▶GWAS Catalog Trait Associations (20)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
GWAS Catalog Trait Associations (20)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
erythrocyte volume
Sakaue S et al. “A cross-population atlas of genetic associations for 220 human phenotypes.” Nature Genetics 53(10):1415-1424 (2021)
Allele T
OR 0.11
p —
N 480,305
Large GWAS
multi-ancestry
Verma A et al. “Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.” Science (new York, N.y.) 385(6706):eadj1182 (2024)
Allele T
OR 0.13
p 9.9e-324
N 583,955
Major Consortium StudyLarge GWAS
multi-ancestry
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.05
p 2.0e-40
N 408,112
Large GWAS
European
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele T
OR 0.07
p 6.0e-237
N 394,642
Large GWAS
European
Thompson A et al. “Assessing the impact of alcohol consumption on the genetic contribution to mean corpuscular volume.” Human Molecular Genetics 30(21):2040-2051 (2021)
Allele T
OR —
β 0.460
p 9.0e-287
N 362,595
Large GWAS
European
Jee YH et al. “Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures.” Nature Communications 16(1):4935 (2025)
Allele T
OR 0.11
p 2.0e-167
N 153,950
Large GWAS
East Asian
Chen MH et al. “Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.” Cell 182(5):1198-1213.e14 (2020)
Allele T
OR 0.12
p 5.0e-15
N 9,298
Large GWAS
Hispanic or Latin American
mean reticulocyte volume
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele T
OR 0.08
p 1.0e-291
N 394,642
Large GWAS
European
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.05
p 1.0e-39
N 408,112
Large GWAS
European
hemoglobin measurement
Jee YH et al. “Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures.” Nature Communications 16(1):4935 (2025)
Allele A
OR 0.04
p 3.0e-145
N 928,679
Large GWAS
multi-ancestry
Oskarsson GR et al. “Predicted loss and gain of function mutations in ACO1 are associated with erythropoiesis.” Communications Biology 3(1):189 (2020)
Allele A
OR —
β 0.037
p 9.0e-50
N 684,122
Large GWAS
European
Verma A et al. “Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.” Science (new York, N.y.) 385(6706):eadj1182 (2024)
Allele A
OR 0.03
p 1.0e-31
N 584,680
Major Consortium StudyLarge GWAS
multi-ancestry
Chen MH et al. “Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.” Cell 182(5):1198-1213.e14 (2020)
Allele A
OR 0.04
p 2.0e-83
N 563,946
Large GWAS
European
Sakaue S et al. “A cross-population atlas of genetic associations for 220 human phenotypes.” Nature Genetics 53(10):1415-1424 (2021)
Allele A
OR 0.03
p 1.0e-68
N 502,921
Large GWAS
multi-ancestry
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele A
OR 0.04
p 1.0e-51
N 408,112
Large GWAS
European
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele A
OR 0.03
p 6.0e-74
N 394,642
Large GWAS
European
Astle WJ et al. “The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.” Cell 167(5):1415-1429.e19 (2016)
Allele A
OR 0.03
p 2.0e-16
N 172,925
Large GWAS
European
Akbari P et al. “A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.” Nature Communications 14(1):5023 (2023)
Allele A
OR 0.11
p 3.0e-38
N 39,127
Large GWAS
European
hematocrit
Jee YH et al. “Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures.” Nature Communications 16(1):4935 (2025)
Allele A
OR 0.03
p 6.0e-144
N 928,679
Large GWAS
multi-ancestry
Verma A et al. “Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.” Science (new York, N.y.) 385(6706):eadj1182 (2024)
Allele A
OR 0.04
p 9.0e-50
N 584,647
Major Consortium StudyLarge GWAS
multi-ancestry
Chen MH et al. “Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.” Cell 182(5):1198-1213.e14 (2020)
Allele A
OR 0.05
p 1.0e-104
N 562,259
Large GWAS
European
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele A
OR 0.03
p 7.0e-20
N 408,112
Large GWAS
European
Astle WJ et al. “The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.” Cell 167(5):1415-1429.e19 (2016)
Allele A
OR 0.04
p 2.0e-25
N 173,039
Large GWAS
European
neutrophil count
Chen MH et al. “Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.” Cell 182(5):1198-1213.e14 (2020)
Allele T
OR —
p 3.0e-49
N 627,215
Large GWAS
multi-ancestry
Sakaue S et al. “A cross-population atlas of genetic associations for 220 human phenotypes.” Nature Genetics 53(10):1415-1424 (2021)
Allele T
OR 0.03
p 2.0e-35
N 432,666
Large GWAS
multi-ancestry
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.04
p 1.0e-46
N 408,112
Large GWAS
European
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele T
OR 0.03
p 4.0e-34
N 394,642
Large GWAS
European
Verma A et al. “Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.” Science (new York, N.y.) 385(6706):eadj1182 (2024)
Allele T
OR 0.03
p 7.0e-23
N 275,053
Major Consortium StudyLarge GWAS
European
mean corpuscular hemoglobin
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.05
p 3.0e-43
N 408,112
Large GWAS
European
myeloid leukocyte count
Chen MH et al. “Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.” Cell 182(5):1198-1213.e14 (2020)
Allele T
OR —
p 1.0e-39
N 746,667
Large GWAS
multi-ancestry
leukocyte quantity
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.03
p 4.0e-34
N 408,112
Large GWAS
European
Jee YH et al. “Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures.” Nature Communications 16(1):4935 (2025)
Allele T
OR 0.02
p 3.0e-31
N 928,679
Large GWAS
multi-ancestry
Verma A et al. “Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.” Science (new York, N.y.) 385(6706):eadj1182 (2024)
Allele T
OR 0.03
p 2.0e-21
N 381,267
Major Consortium StudyLarge GWAS
European
Sakaue S et al. “A cross-population atlas of genetic associations for 220 human phenotypes.” Nature Genetics 53(10):1415-1424 (2021)
Allele T
OR 0.02
p 4.0e-8
N 154,355
Large GWAS
East Asian
cysteine-rich secretory protein 3 measurement
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele T
OR 0.05
p 3.0e-27
N 47,745
Large GWAS
European
erythropoietin level
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele T
OR 0.07
p 2.0e-24
N 47,745
Large GWAS
European
This variant is in our database but has no known associations or PRS memberships yet.
Gene information from NCBI Gene. Variant classifications from ClinVar.
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