Table 2 Genetic associations between polymorphisms in IGF1/IGFBP3 and risk of renal cell carcinoma.

From: Genetic variation in IGF1 predicts renal cell carcinoma susceptibility and prognosis in Chinese population

The best genetic model*

Stages

SNPs

Location

Cases†

Controls†

MAF

P for HWE

P

OR

Test set

 IGF1

rs6214 G > A

3′ UTR

90/168/97

109/182/71

0.447

0.750

0.015

0.65 (0.45–0.86)

rs6218 T > C

3′ UTR

207/125/23

207/143/12

0.231

0.032

0.760

0.94 (0.69–1.29)

rs35767 C > T

5′ near gene

152/152/51

165/160/37

0.323

0.885

0.456

1.13 (0.82–1.55)

rs5742612 T > C

5′ near gene

194/140/21

209/137/17

0.236

0.360

0.448

1.26 (0.97–1.86)

rs5742714 G > C

3′ UTR

249/99/7

225/114/23

0.221

0.104

0.024

0.66 (0.48–0.92)

 IGFBP3

rs2132572 G > A

5′ near gene

224/116/15

240/111/11

0.184

0.670

0.370

1.07 (0.77–1.47)

rs2854744 A > C

5′ near gene

208/114/33

198/142/22

0.257

0.602

0.293

0.82 (0.60–1.12)

rs2854746 C > G

Missense

217/108/30

228/118/16

0.207

0.883

0.608

1.12 (0.82–1.55)

rs282734 A > C

Missense

323/30/2

325/36/1

0.052

0.997

0.584

0.77 (0.46–1.29)

Validation

 IGF1

rs5742714

3′ UTR

464/180/28

466/241/25

0.199

0.363

0.040

0.79 (0.63–0.98)

rs6214 G > A

3′ UTR

193/326/153

192/368/172

0.486

0.866

0.239

0.86 (0.68–1.10)

Combined

 IGF1

rs5742714

3′ UTR

713/279/35

691/355/48

0.206

0.779

0.002

0.82 (0.68–0.98)

  1. OR, odds ratio; HWE (Hardy–Weinberg equilibrium) test among controls; Values in bold indicate they are statistically different.
  2. *Logistic regression model with adjustment for age, sex, BMI, smoking status, drinking status, hypertension, diabetes and family history of cancer; detail information on the results the SNPs were demonstrated in Supplemental Table 1. All the best genetic model of the SNPs was recessive model, except for rs6214, of which the best genetic model was dominant model.
  3. †Major homozygote/heterozygote/minor homozygote between cases and controls.
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