rs13108218
▶GWAS Catalog Trait Associations (213)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
GWAS Catalog Trait Associations (213)
Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.
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 A
OR 0.05
p 4.0e-231
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 A
OR 0.02
p 2.0e-28
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 A
OR 0.04
p 3.0e-84
N 435,807
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 0.03
p 3.0e-22
N 372,982
Major Consortium StudyLarge GWAS
European
Harrison S et al. “Testosterone and socioeconomic position: Mendelian randomization in 306,248 men and women in UK Biobank.” Science Advances 7(31) (2021)
Allele A
OR 0.11
p 4.0e-18
N 148,248
Major Consortium StudyLarge GWAS
European
Karjalainen MK et al. “Genome-wide characterization of circulating metabolic biomarkers.” Nature 628(8006):130-138 (2024)
Allele A
OR 0.03
p 2.0e-13
N 136,016
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 A
OR 0.03
p 4.0e-10
N 115,064
Large GWAS
European
triglyceride 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 1.0e-163
N 928,679
Large GWAS
multi-ancestry
Graham SE et al. “The power of genetic diversity in genome-wide association studies of lipids.” Nature 600(7890):675-679 (2021)
Allele A
OR 0.03
p 7.0e-57
N 1,320,016
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 3.0e-28
N 558,637
Major Consortium StudyLarge 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 A
OR 0.03
p 4.0e-53
N 455,659
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 A
OR 0.03
p 3.0e-38
N 450,015
Large GWAS
multi-ancestry
Richardson TG et al. “Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis.” Plos Medicine 17(3):e1003062 (2020)
Allele A
OR 0.03
p 8.0e-50
N 441,016
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 1.0e-51
N 394,642
Large GWAS
European
Koskeridis F et al. “Pleiotropic genetic architecture and novel loci for C-reactive protein levels.” Nature Communications 13(1):6939 (2022)
Allele A
OR 0.03
p 2.0e-26
N 361,194
Large GWAS
European
Klarin D et al. “Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program.” Nature Genetics 50(11):1514-1523 (2018)
Allele A
OR 0.02
p 1.0e-16
N 297,626
Major Consortium StudyLarge GWAS
multi-ancestry
Karjalainen MK et al. “Genome-wide characterization of circulating metabolic biomarkers.” Nature 628(8006):130-138 (2024)
Allele A
OR 0.03
p 1.0e-11
N 136,016
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 A
OR 0.04
p 4.0e-19
N 115,082
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 A
OR 0.04
p 2.0e-15
N 88,329
Large GWAS
European
de Vries PS et al. “Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions.” American Journal of Epidemiology 188(6):1033-1054 (2019)
Allele A
OR —
β 0.020
p 1.0e-12
N 71,394
Large GWAS
multi-ancestry
platelet 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 A
OR 0.03
p 1.0e-82
N 928,679
Large GWAS
multi-ancestry
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 0.02
p 3.0e-26
N 394,642
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 A
OR —
p 2.0e-12
N 235,256
Large GWAS
European
total cholesterol 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 0.03
p 2.0e-79
N 928,679
Large GWAS
multi-ancestry
Graham SE et al. “The power of genetic diversity in genome-wide association studies of lipids.” Nature 600(7890):675-679 (2021)
Allele A
OR 0.03
p 2.0e-49
N 1,320,016
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 0.02
p 8.0e-25
N 480,086
Large GWAS
multi-ancestry
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 0.02
p 2.0e-25
N 394,642
Large GWAS
European
glycoprotein measurement
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele G
OR 0.04
p 6.0e-75
N 450,015
Large GWAS
multi-ancestry
Yuan F et al. “Blood metabolic biomarkers and colorectal cancer risk: results from large prospective cohort and Mendelian randomisation analyses.” British Journal of Cancer 133(1):94-103 (2025)
Allele G
OR 0.04
p 3.0e-32
N 199,732
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 0.04
p 5.0e-20
N 115,082
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 0.04
p 1.0e-17
N 88,329
Large GWAS
European
concentration of small HDL particles measurement
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele G
OR 0.04
p 3.0e-73
N 450,015
Large GWAS
multi-ancestry
triglycerides to total lipids in very large HDL percentage
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele G
OR 0.03
p 1.0e-70
N 450,015
Large GWAS
multi-ancestry
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 0.04
p 3.0e-16
N 88,307
Large GWAS
European
calcium measurement
Sakaue S et al. “A cross-population atlas of genetic associations for 220 human phenotypes.” Nature Genetics 53(10):1415-1424 (2021)
Allele G
OR 0.04
p 2.0e-67
N 399,133
Large GWAS
multi-ancestry
Loya H et al. “A scalable variational inference approach for increased mixed-model association power.” Nature Genetics 57(2):461-468 (2025)
Allele G
OR 0.03
p 5.0e-59
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 G
OR 0.03
p 7.0e-17
N 355,605
Major Consortium StudyLarge GWAS
multi-ancestry
Young WJ et al. “Genetically Determined Serum Calcium Levels and Markers of Ventricular Repolarization: A Mendelian Randomization Study in the UK Biobank.” Circulation. Genomic and Precision Medicine 14(3):e003231 (2021)
Allele G
OR 0.00
p 3.0e-51
N 305,349
Major Consortium StudyLarge GWAS
European
total lipids in small HDL measurement
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele G
OR 0.04
p 8.0e-66
N 450,015
Large GWAS
multi-ancestry
Karjalainen MK et al. “Genome-wide characterization of circulating metabolic biomarkers.” Nature 628(8006):130-138 (2024)
Allele G
OR 0.03
p 2.0e-14
N 136,016
Large GWAS
multi-ancestry
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 0.04
p 2.0e-15
N 88,329
Large GWAS
European
phospholipids:total lipids ratio
Zoodsma M et al. “A genetic map of human metabolism across the allele frequency spectrum.” Nature Genetics 57(10):2445-2455 (2025)
Allele G
OR 0.03
p 8.0e-65
N 450,015
Large GWAS
multi-ancestry
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 0.04
p 2.0e-15
N 88,329
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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