Characteristics of cases and controls
We recruited 506 RA patients consisting of 135 males and 371 females (mean age 54.35 ± 11.69 years). And 509 unrelated healthy individuals consisting of 134 males and 375 females were used as the controls (mean age 54.39 ± 12.02 years). There was no statistically significant difference on distribution of gender between the case and control group (p > 0.958). However, the distribution of age was significant difference (p = 0.038). In addition, we analyzed the clinical parameters in the cases. The mean ± SD of CRP and RF among 506 cases were 31.05 ± 40.25 mg/L and 164.09 ± 147.21 KIU/L, respectively. And the mean ± SD of ESR and CCP in the cases were 44.28 ± 30.86 mm/h and 75.11 ± 60.78 RU/ml. The detailed characteristics of cases and controls were showed in Table 1.
Association between FCGR2A variations and RA risk
The basic information of four FCGR2A polymorphisms is shown in Table 2. The genotype distribution of all SNPs in the control group was in accordance with HWE (p > 0.05). The minor allele “A” of rs6668534 was significantly related to an increased risk of RA in the Han Chinese population (OR = 1.24, 95% CI = 1.04 – 1.48, p = 0.014). Genetic models (including the codominant, the dominant, the recessive, and the log-additive model) were applied for further exploration of the relationship between FCGR2A variations and RA risk in this study (Table 3). Our result showed that the rs6668534 was associated with a 1.51-fold increased risk of RA in the codominant model (adjusted, 95% CI = 1.07 – 2.12, p = 0.018 for the “A/A” genotype), 1.35 - fold increased risk of RA in the recessive model (adjusted, 95% CI = 1.02 – 1.78, p = 0.034 for the “A/A” genotype), and 1.23 - fold increased risk of RA in the log-additive model (adjusted, 95% CI = 1.04 – 1.46, p = 0.018), respectively. However, we had not found that any correlation between other three SNPs and RA risk with or without adjustment by age and gender.
Stratification analysis by gender and age
The stratification analysis by gender and age between the four SNPs and RA risk were displayed in Table 4. After the stratification analysis by gender adjusted for age, we found only rs6668534 was correlated with improved risk of RA in males in the allele model (OR = 1.50, 95% CI = 1.07 – 2.10, p = 0.020), the codominant model (adjusted, OR = 2.33, 95% CI = 1.29 – 4.22, p = 0.005 for the “G/A” genotype; OR = 2.16, 95% CI = 1.10 – 4.24, p = 0.026 for the “A/A” genotype), the dominant model (adjusted, OR = 2.27, 95% CI = 1.30 – 3.95, p = 0.004), and the log-additive model (adjusted, OR = 1.47, 95% CI = 1.05 – 2.06, p = 0.023). However, there was no significant differences between the female subgroup in any genetic model.
Then, we conducted stratification analysis by age of 54 years old adjusted for age and gender. There was no significant association between SNPs and RA risk at age > 54 years old. But two SNPs (rs6671847 and rs1801274) were observed to be associated with the risk of RA at age ≤54 years old based on the results of the allele model (rs6671847, OR = 0.72, 95% CI = 0.55 – 0.94, p = 0.014; rs1801274, OR = 0.73, 95% CI = 0.56 – 0.94, p = 0.017), the codominant model (rs6671847, OR = 0.50, 95% CI = 0.27 – 0.90, p = 0.020; rs1801274, OR = 0.50, 95% CI = 0.28 – 0.90, p = 0.022), and the log-additive model (rs6671847, OR = 0.72, 95% CI = 0.55 – 0.94, p = 0.016; rs1801274, OR = 0.73, 95% CI = 0.56 – 0.95, p = 0.019).
Furthermore, the relationship between genotypes at different loci and clinical parameters among patients were analyzed, as listed in Table 5. Our results showed that RA patients with different genotype of rs6671847 and rs1801274 had significantly different RF and CCP level (rs6671847, p = 0.003, p = 0.015; rs1801274, p = 0.002, p = 0.014, respectively). Similarly, the genotypes of rs6668534 in the RA patients showed significantly different CRP and CCP level (p = 0.029, p = 0.028, respectively).
LD and Haplotype analysis
We further performed the LD analysis among the four SNPs (rs6671847, rs1801274, rs17400517, and rs6668534) in FCGR2A. A strong linkage in block 1 between rs6671847 and rs1801274 was found (Figure 1). Unfortunately, there was no statistically difference between the cases and controls among the FCGR2A haplotypes (Table 6).