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. 2018 May 3;15:34. doi: 10.1186/s12986-018-0270-2

Table 4.

Associations of the 11 SNPs with FPG in 2030 Chinese children

SNP Nearest gene Unadjusted for age- and sex-specific WHR-Z scores Adjusted for age- and sex-specific WHR-Z scores
β (S.E.) P-value β (S.E.) P-value
rs984222 TBX15-WARS2 −0.033 (0.016) 0.043* − 0.032 (0.016) 0.045*
rs1011731 DNM3-PIGC 0.035 (0.024) 0.137 0.031 (0.024) 0.192
rs4846567 LYPLAL1 −0.015 (0.017) 0.390 −0.013 (0.017) 0.455
rs10195252 GRB14 0.010 (0.026) 0.704 0.011 (0.025) 0.671
rs6795735 ADAMTS9 0.033 (0.018) 0.078 0.032 (0.018) 0.083
rs1294421 LY86 0.010 (0.019) 0.597 0.011 (0.019) 0.565
rs6905288 VEGFA −0.011 (0.018) 0.553 −0.011 (0.018) 0.545
rs9491696 RSPO3 0.020 (0.016) 0.196 0.021 (0.016) 0.174
rs1055144 NFE2L3 0.018 (0.016) 0.253 0.021 (0.016) 0.181
rs1443512 HOXC13 0.013 (0.020) 0.524 0.012 (0.020) 0.543
rs4823006 ZNRF3-KREMEN1 −0.007 (0.016) 0.677 −0.005 (0.016) 0.751
Unweighted GRS 0.004 (0.006) 0.464 0.005 (0.006) 0.391
Weighted GRS 0.004 (0.006) 0.502 0.004 (0.006) 0.418

Linear regression was performed to examine the independent and cumulative effects of each SNP on FPG under an additive model adjusted for study group, sex, age and age squared, without or with adjustment for age- and sex-specific WHR-Z scores

FPG fasting plasma glucose, GRSgenetic risk score, SNP single nucleotide polymorphism, S.E standard error, WHR waist-hip ratio

*Two-sided P < 0.05