rs2867125

This is a intergenic variant variant.

GWAS Catalog Trait Associations (7)

Genome-wide significant associations (p < 5×10⁻⁸) from the NHGRI-EBI GWAS Catalog.

smoking initiation

Saunders GRB et al. Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 612(7941):720-724 (2022)
Allele C
OR 0.02
p 5.0e-52
N 3,382,012
Large GWAS
European, East Asian, Hispanic or Latin American, African unspecified

physical activity measurement, body mass index

Allele C
OR 0.07
p 1.0e-49
N 161,368
Meta-analysisLarge GWAS
multi-ancestry

cigarettes per day measurement

Saunders GRB et al. Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 612(7941):720-724 (2022)
Allele C
OR 0.02
p 4.0e-11
N 618,489
Large GWAS
European

type 2 diabetes mellitus

Allele T
OR 0.06
p 4.0e-10
N 659,316
Large GWAS
multi-ancestry
Allele T
OR 1.06
p 2.0e-9
N 183,651
Large GWAS
multi-ancestry

body mass index

Allele C
OR
β 0.051
p 2.0e-30
N 197,610
Large GWAS
European
Allele C
OR 0.31
p 3.0e-49
N 123,865
Large GWAS
European
Allele C
OR 0.08
p 7.0e-11
N 38,595
Meta-analysisLarge GWAS
multi-ancestry

Research that mentions this SNP (4)

Association of the LINGO2-related SNP rs10968576 with body mass in a cohort of elderly Swedes
AssociationN=949Mathias Rask-Andersen et al.(2015)· Molecular Genetics and Genomics

Association study of 35 GWAS-identified body mass SNPs in 949 elderly Swedish participants (mean age 70-75 years). Significant association found between rs10968576 (LINGO2, intron 4) and BMI with a larger effect size (β = 0.69 kg/m²) than reported in younger populations, suggesting age-specific genetic effects on body mass in the elderly.

Traits studied:Body Mass IndexBody adiposityObesityOverweight
Common obesity risk alleles in childhood attention‐deficit/hyperactivity disorder
AssociationN=4,415Özgür Albayrak et al.(2013)· American Journal of Medical Genetics Part B: Neuropsychiatric Genetics

This study examined whether 32 obesity-associated genetic risk alleles are associated with childhood ADHD in a German GWAS sample (495 cases, 1,300 controls) and a meta-analysis (2,064 trios, 896 cases, 2,455 controls). The obesity risk allele G at rs206936 in NUDT3 was associated with increased ADHD risk (OR=1.39, P=3.4×10⁻⁴), and rs6497416 in GPRC5B showed association with ADHD in the meta-analysis (P=7.2×10⁻⁴). Several obesity-related SNPs were associated with ADHD endophenotypes including inattention and hyperactivity/impulsivity.

Traits studied:Attention-deficit/hyperactivity disorder (ADHD)Body mass index (BMI)Hyperactivity/impulsivityInattentionObesity
Associations of polymorphisms in the genes of FGFR2, FGF1, and RBFOX2 with breast cancer risk by estrogen/progesterone receptor status
AssociationN=2,416Yu‐Ling Cen et al.(2013)· Molecular Carcinogenesis

A hospital-based case-control study in rural and urban India (1,204 cases; 1,212 controls) examined genetic and lifestyle risk factors for breast cancer. Four SNPs in FGFR2 (rs1219648, rs2420946, rs2981575, rs2981582) showed positive associations with breast cancer (ORs 1.32-1.47). Additional SNPs in obesity and metabolic genes (rs374748 in FBN2, rs2922763 in HNF4G, rs2116830 in KCNMA1, rs11121832 in MTHFR, rs16886165 in MAP3K1, rs11594610 in TCF7L2, rs2274459 in MLN) were associated with increased breast cancer risk. Waist-to-hip ratio ≥0.95 showed strong association (OR 3.78; 95% CI 2.92-4.89), and women living first 20 years in rural areas showed protective effect (OR 0.77).

Traits studied:Breast cancerBreast cancer riskER+/PR+ breast cancerER/PR negative breast cancerTriple negative breast cancer
Obesity-susceptibility loci and the tails of the pediatric BMI distribution
AssociationN=7,225Jonathan A. Mitchell et al.(2013)· Obesity

This study examined 8 adult obesity-susceptibility loci in 7,225 children aged 2-18 years using quantile regression to assess whether genetic effects on BMI are uniform across the BMI distribution. The authors found that obesity risk alleles (FTO rs3751812, MC4R rs12970134, TMEM18 rs2867125, BDNF rs6265, SEC16B rs10913469, GNPDA2 rs13130484, NRXN3 rs10146997, and TNNI3K rs1514175) were more strongly associated with BMI increases at the upper tail of the distribution (85th-95th percentiles, β=0.06-0.11, p<10^-6) compared to the lower tail, suggesting that standard linear regression approaches may underestimate genetic effects on childhood obesity.

Traits studied:BMIChildhood obesityObesity

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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