TABLE 2

Associations of SNPs with overweight and obesity in multinomial logistic regression with age and sex adjustment

SNPChr.Nearest geneEffect alleleOther alleleOverweight (n = 655) vs. normal weight (n = 1,619)Obese (n = 1,229) vs. normal weight (n = 1,619)
OR (additive model)Lower bound of one-sided 95% CINominal PPermuted POR (additive model)Lower bound of one-sided 95% CINominal PPermuted PReported OR (95% CI)
rs713880312FAIM2AG1.120.990.0560.261.151.040.0200.111.14 (1.09–1.19)
rs180508118NPC1AG0.950.830.200.481.121.010.0480.231.33 (1.07–1.75)
rs649964016FTOAG1.030.890.380.501.191.050.0160.0881.16 (1.10–1.21)
rs1778231318MC4RCT1.261.100.00210.0131.371.238.2 × 10−75.0 × 10−61.20 (1.09–1.31)
rs626511BDNFGA1.050.940.210.481.161.060.00750.0431.12 (1.06–1.19)
rs109383974GNPDA2GA1.121.000.0570.261.241.130.000140.000851.20 (1.09–1.31)
  • Nominal P values were adjusted for age and sex, and permuted P values were further corrected for multiple testing. All P values were one-sided. Obese, overweight, and normal-weight children were diagnosed by the Chinese age- and sex-specific BMI cutoffs (supplementary Table 1) (13). ORs and 95% CIs were calculated using multinomial logistic regression with genotypes, age, and sex as the independent variables. Chr., chromosome.