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. 2017 Apr 26;6:11. doi: 10.1186/s40035-017-0081-9

Table 4.

Demographic and clinical features of patients with two combined SNPs

Characteristics rs4633 C > T; rs4680 G > A rs6269 A > G; rs4818 C > G
CC/GG CT/GA TT/AA Rare P AA/CC AG/CG GG/GG Rare P
n 78 55 8 2 61 64 13 5
H&Y stageb 2.0 ± 1.5 2.0 ± 1.0 2.8 ± 0.5 2.50 ± 1.0 0.03* 2.5 ± 1.0 2.0 ± 1.0 2.0 ± 0.8 2.0 ± 1.5 0.12
Age onset (years)a 60.7 ± 9.2 57.5 ± 9.5 56.8 ± 5.7 58.0 ± 5.7 0.03* 59.4 ± 9.6 58.6 ± 8.8 60.8 ± 10.9 60.8 ± 5.1 0.71
Disease duration (years)b 6.0 ± 4.0 6.0 ± 6.0 8.5 ± 9.5 9.0 ± 4.0 0.02* 6.0 ± 5.5 6.0 ± 5.3 8.0 ± 8.5 4.0 ± 3.5 0.67
LED (mg)a 386.2 ± 287.5 494.0 ± 360.7 692.4 ± 344.8 675.0 ± 35.4 0.01* 479.0 ± 401.5 431.8 ± 241.4 416.4 ± 342.2 448.8 ± 327.4 0.67
Wearing-off (yes, %) 18 (23.1) 19 (34.6) 5 (62.5) 1(50.0) 0.02* 20 (32.8) 17 (26. 6) 5 (38.5) 1 (20.0) 0.87
Dyskinesia (yes, %) 7 (9.0) 9 (16.4) 2 (25.0) 0 0.07 8 (13.1) 7 (10.9) 3 (23.1) 0 0.52
UPDRS Part I scoreb 2.0 ± 3.0 3.0 ± 3.0 2.0 ± 3.5 3.0 ± 0.0 0.98 2.0 ± 4.0 2.0 ± 3.0 3.0 ± 3.0 3.0 ± 5.5 0.50
UPDRS Part II scoreb 8.5 ± 9.0 8.0 ± 6.0 13.0 ± 7.8 13.5 ± 17.0 0.03* 8.0 ± 7.0 8.5 ± 7.0 9.0 ± 7.5 10.0 ± 13.0 0.77
UPDRS Part III scorea 25.9 ± 11.9 21.9 ± 11.7 31.0 ± 11.9 32.0 ± 21.2 0.08 25.1 ± 12.3 24.5 ± 12.2 26.2 ± 10.3 19.4 ± 14. 9 0.83
UPDRS Part IV scoreb 3.0 ± 2.0 2.0 ± 3. 0 4.5 ± 4.0 4.0 ± 2.0 0.24 3.0 ± 3.5 2.0 ± 2.8 3.0 ± 2.0 2.0 ± 4.0 0.78
UPDRS total scorea 41.0 ± 17.4 36.4 ± 16.6 52.0 ± 19.7 52.5 ± 34.7 0.047* 40.5 ± 18.6 39.1 ± 17.2 44.1 ± 15.5 34.6 ± 20.4 0.86
NMS scoreb 6.0 ± 6.0 6.0 ± 4.0 6.5 ± 10.8 6.5 ± 9.0 0.85 7.0 ± 6.5 6.0 ± 5.75 6.0 ± 6.0 9.0 ± 11.0 0.46
HAMA scoreb 4.0 ± 6.0 5.0 ± 5.0 4.5 ± 13.3 3.0 ± 4.0 0.29 5.0 ± 6.0 4.0 ± 4.0 6.0 ± 6.0 8.0 ± 12.5 0.20
HAMD scoreb 2.0 ± 5.0 4.0 ± 4.0 3.0 ± 6.5 2.0 ± 4.0 0.56 2.0 ± 6.5 3.0 ± 4.0 2.0 ± 2.0 7.0 ± 7.5 0.86
MMSE scoreb 28.0 ± 3.0 28.0 ± 3.0 27.5 ± 3.0 26.5 ± 3.0 0.72 28.0 ± 3.0 28.0 ± 3.0 28.0 ± 3.0 29.0 ± 2.0 0.37

Data were analyzed with analysis of variance of factorial design with age and sex as covariates

Binary logistic regression model was used to analyze the relation between SNP and motor complication (wearing-off phenomenon and dyskinesia), with age and sex as covariates

*P < 0.05, aValues are expressed as the mean ± SD; bValues are expressed as the median ± IQ