rs79687284
This is a regulatory region variant variant in the PROX1-AS1 gene.
▶GWAS Catalog Trait Associations (11)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
GWAS Catalog Trait Associations (11)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
glutamine measurement
Richardson TG et al. “Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation.” Plos Biology 20(2):e3001547 (2022)
Allele G
OR 0.16
p 4.0e-43
N 114,751
Large GWAS
European
Abar L et al. “Unravelling genetic architecture of circulatory amino acid levels, and their effect on risk of complex disorders.” Nar Genomics and Bioinformatics 6(2):lqae046 (2024)
Allele G
OR 0.15
p 9.0e-43
N 117,944
Large GWAS
European
Davyson E et al. “Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids.” Biological Psychiatry 94(8):630-639 (2023)
Allele G
OR 0.16
p 2.0e-36
N 88,070
Large GWAS
European
Lotta LA et al. “A cross-platform approach identifies genetic regulators of human metabolism and health.” Nature Genetics 53(1):54-64 (2021)
Allele G
OR 8.07
p 7.0e-16
N 85,821
Large GWAS
European
glucose measurement
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele C
OR 0.07
p 5.0e-36
N 394,642
Large GWAS
European
Lagou V et al. “GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification.” Nature Genetics 55(9):1448-1461 (2023)
Allele C
OR 0.01
p 2.0e-26
N 475,416
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 C
OR 0.08
p 1.0e-33
N 448,252
Large GWAS
multi-ancestry
Richardson TG et al. “Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation.” Plos Biology 20(2):e3001547 (2022)
Allele C
OR 0.07
p 2.0e-10
N 114,870
Large GWAS
European
alanine measurement
Richardson TG et al. “Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation.” Plos Biology 20(2):e3001547 (2022)
Allele G
OR 0.14
p 2.0e-34
N 115,078
Large GWAS
European
Abar L et al. “Unravelling genetic architecture of circulatory amino acid levels, and their effect on risk of complex disorders.” Nar Genomics and Bioinformatics 6(2):lqae046 (2024)
Allele G
OR 0.13
p 2.0e-31
N 117,944
Large GWAS
European
Davyson E et al. “Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids.” Biological Psychiatry 94(8):630-639 (2023)
Allele G
OR 0.14
p 1.0e-33
N 88,325
Large GWAS
European
type 2 diabetes mellitus
Huerta-Chagoya A et al. “Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.” Nature Genetics 56(11):2370-2379 (2024)
Allele G
OR 0.25
p 2.0e-30
N 421,743
Large GWAS
multi-ancestry
Mahajan A et al. “Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.” Nature Genetics 50(11):1505-1513 (2018)
Allele G
OR 1.16
p 3.0e-16
N 898,130
Large GWAS
European
Mahajan A et al. “Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.” Nature Genetics 54(5):560-572 (2022)
Allele G
OR 0.15
p 2.0e-16
N 251,740
Large GWAS
European
tyrosine measurement
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele C
OR 0.06
p 3.0e-27
N 450,015
Large GWAS
multi-ancestry
serum albumin amount
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 C
OR 0.06
p 8.0e-20
N 928,679
Large GWAS
multi-ancestry
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele C
OR 0.04
p 5.0e-15
N 450,015
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 C
OR 0.05
p 4.0e-13
N 435,807
Large GWAS
multi-ancestry
leucine measurement
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele C
OR 0.04
p 6.0e-14
N 450,015
Large GWAS
multi-ancestry
glycine measurement
Abar L et al. “Unravelling genetic architecture of circulatory amino acid levels, and their effect on risk of complex disorders.” Nar Genomics and Bioinformatics 6(2):lqae046 (2024)
Allele G
OR 0.06
p 1.0e-10
N 117,944
Large GWAS
European
Richardson TG et al. “Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation.” Plos Biology 20(2):e3001547 (2022)
Allele G
OR 0.07
p 2.0e-10
N 114,978
Large GWAS
European
Davyson E et al. “Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids.” Biological Psychiatry 94(8):630-639 (2023)
Allele G
OR 0.08
p 2.0e-10
N 88,258
Large GWAS
European
Drugs used in diabetes use measurement
Wu Y et al. “Genome-wide association study of medication-use and associated disease in the UK Biobank.” Nature Communications 10(1):1891 (2019)
Allele C
OR 0.20
p 3.0e-10
N 305,913
Major Consortium StudyLarge GWAS
European
blood glucose amount
Nagy R et al. “Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants.” Genome Medicine 9(1):23 (2017)
Allele C
OR 0.20
p 2.0e-8
N 29,900
Major Consortium StudyLarge 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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