rs3811444
This is a protein-altering variant in the TRIM58 gene.
▶GWAS Catalog Trait Associations (60)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
GWAS Catalog Trait Associations (60)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
reticulocyte amount
Vuckovic D et al. “The Polygenic and Monogenic Basis of Blood Traits and Diseases.” Cell 182(5):1214-1231.e11 (2020)
Allele T
OR 0.10
p —
N 408,112
Large GWAS
European
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 0.07
p 1.0e-272
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 0.08
p 5.0e-255
N 408,112
Large GWAS
European
Red cell distribution width
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-232
N 394,642
Large GWAS
European
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 8.0e-224
N 563,352
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 0.07
p 7.0e-184
N 408,112
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 0.04
p 2.0e-49
N 380,796
Major Consortium StudyLarge GWAS
European
Pilling LC et al. “Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers.” Plos One 12(9):e0185083 (2017)
Allele T
OR 0.07
p 6.0e-59
N 116,666
Large GWAS
European
level of golgin subfamily A member 3 in blood
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 0.17
p 5.0e-151
N 47,745
Large GWAS
European
junctional adhesion molecule B 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 0.13
p 2.0e-124
N 47,745
Large GWAS
European
erythrocyte count
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 0.03
p 6.0e-106
N 928,679
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 1.0e-67
N 503,987
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 2.0e-77
N 408,112
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 0.04
p 5.0e-60
N 405,366
Major Consortium StudyLarge 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 5.0e-78
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 T
OR 0.04
p 1.0e-29
N 172,952
Large GWAS
European
van der Harst P et al. “Seventy-five genetic loci influencing the human red blood cell.” Nature 492(7429):369-75 (2012)
Allele T
OR 0.02
p 5.0e-10
N 71,861
Large GWAS
multi-ancestry
platelet count
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 0.04
p 1.0e-95
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 0.03
p 3.0e-31
N 408,112
Large GWAS
European
Kachuri L et al. “Genetic determinants of blood-cell traits influence susceptibility to childhood acute lymphoblastic leukemia.” American Journal of Human Genetics 108(10):1823-1835 (2021)
Allele T
OR —
p 2.0e-36
N 235,256
Large GWAS
European
Gieger C et al. “New gene functions in megakaryopoiesis and platelet formation.” Nature 480(7376):201-8 (2011)
Allele T
OR 3.35
p 6.0e-9
N 48,666
Large GWAS
European
spermidine measurement
Surendran P et al. “Rare and common genetic determinants of metabolic individuality and their effects on human health.” Nature Medicine 28(11):2321-2332 (2022)
Allele T
OR 0.26
p 3.0e-80
N 14,296
Large GWAS
European
Hysi PG et al. “Metabolome Genome-Wide Association Study Identifies 74 Novel Genomic Regions Influencing Plasma Metabolites Levels.” Metabolites 12(1) (2022)
Allele T
OR 0.11
p 5.0e-12
N 8,809
Large GWAS
European
Chen Y et al. “Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases.” Nature Genetics 55(1):44-53 (2023)
Allele T
OR 0.11
p 7.0e-11
N 7,348
Large GWAS
European
Feofanova EV et al. “Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.” Nature Communications 14(1):3111 (2023)
Allele T
OR 0.28
p 7.0e-42
N 5,981
Large GWAS
multi-ancestry
level of clathrin light chain A in blood
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 0.12
p 3.0e-70
N 47,745
Large GWAS
European
level of elongation factor 1-delta in blood serum
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 0.11
p 2.0e-66
N 47,745
Large GWAS
European
About TRIM58
Predicted to enable ubiquitin protein ligase activity. Predicted to be involved in innate immune response and regulation of gene expression. Predicted to be active in cytoplasm. [provided by Alliance of Genome Resources, Jul 2025]
View all TRIM58 variants →Gene information from NCBI Gene. Variant classifications from ClinVar.
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