Due to privacy concerns in the genome-wide association studies of rheumatoid arthritis，there has been applying differential privacy to protect phenotype information (disease status) from being leaked while returning highly associated SNP（Single-Nucleotide Polymorphism). The trade-off between privacy protection intensity and data availability is a great problem. In order to solve the problem，a novel differential privacy protection method based on EWT (Empirical Wavelet Transform) was proposed. This method achieved the balance between privacy protection intensity and data availability by processing the noise introduced by differential privacy. Firstly，the data with differential privacy noise mechanism was processed by EWT approach; secondly，the kurtosis values of each EWT component were calculated，then some account of noise components was filtered out. At last，the data was reconstructed. After the above steps，the new data was obtained; it would be sorted according to the correlation degree of pathogenic genes. The experimental results show that the novel method can improve the data availability while ensuring the differential privacy protection intensity，and achieve a reasonable trade-off between the privacy protection intensity and the data availability.