Serum metabolomics analysis of deficiency pattern and excess pattern in patients with rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a chronic and refractory autoimmune disease. Deficiency pattern (DP) and excess pattern (EP), as crucial types of Chinese medicine pattern diagnoses published by International Classification of Diseases 11th Revision (ICD-11), could provide new strategies for RA diagnosis. However, the biological basis of DP and EP of RA is not explicit.

Methods

19 female RA DP patients, 41 female RA EP patients and 30 female healthy participants were included in the study. The serums of participants were collected and analyzed by metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to profile metabolic characteristics of RA DP and EP. Furthermore, bioinformatics analysis results were obtained by using Ingenuity Pathway Analysis (IPA) and statistical analysis was performed by SAS version 9.4 for further identification of potential biomarkers.

Results

Serum metabolic profiling revealed 25 and 24 differential metabolites in RA DP and EP respectively, and 19 metabolites were common to RA DP and EP. Compared with DP group, L-Homocysteic acid, LysoPE(P-16:0/0:0), N(omega)-Hydroxyarginine and LysoPC(16:0/0:0) decreased (P < 0.05), and Pyruvic acid, D-Ribose, Gamma-Glutamylserine, PE(22:0/24:1(15Z)), Inosinic acid increased (P < 0.05) in EP group. Menawhile, S-Nitrosoglutathione, 5-Thymidylic acid, SN38 glucuronide, PE(22:0/24:0), PC(24:0/24:1(15Z)) and Bisdiphosphoinositol tetrakisphosphate increased significantly in DP group compared to EP group (P < 0.05). For the unique metabolites, bioinformatics analysis results showed that 5-Methoxytryptamine involved in Melatonin Degradation II and Superpathway of Melatonin Degradation is the key metabolite to RA DP. Meanwhile, GABA is the key metabolite in EP group, which involved in Glutamate Dependent Acid Resistance, GABA Receptor Signaling, Glutamate Degradation III (via 4-aminobutyrate) and 4-aminobutyrate Degradation I. Bioinformatics analysis between unique metabolites of RA DP and EP groups with human target genes for RA showed that 5-methoxytryptamine and LysoPC(18:1(9Z)/0:0), the unique metabolites of RA DP, might participate in colorectal cancer metastasis signaling, tumor microenvironment pathway, apoptosis signaling, MYC mediated apoptosis signaling, erythropoietin signaling pathway and LXR/RXR activation. Simultaneously, GABA, LysoPA(18:1(9Z)/0:0) and L-Targinine, the unique metabolites of RA EP, might participate in neuroinflammation signaling pathway, osteoarthritis pathway, glucocorticoid receptor signaling, ILK signaling, IL-17 signaling and HIF1α signaling.

Conclusions

The study indicates that serum metabolomics preliminarily revealed the biological basis of RA DP and EP. 5-methoxytryptamine, LysoPC(18:1(9Z)/0:0) and GABA, LysoPA(18:1(9Z)/0:0), L-Targinine might be the predictors to distinguish the DP and EP of RA respectively. These interesting results provide thoughts for further study of traditional medicine patterns of ICD-11. It also contributes to provide strategy for personalized precision treatment of RA and further validation is needed.

Validation of the qi blood yin yang deficiency questionnaire on chronic fatigue

Background

Chronic fatigue (CF) reflects an imbalance of inter-organ functions or of the four essential physiological components qi, blood (xue), yin, and yang. CF can be subdivided into different patterns. However, there are no diagnostic methods for CF. This study aimed to clinically validate a pattern identification method by identifying correlations between CF and responses to the qi blood yin yang deficiency questionnaire (QBYY-Q).

Methods

Participants were recruited between May and June 2014 through the Kyung Hee University Korean Medicine hospital website and via posters and comprised 129 CF patients diagnosed with the United States Centers for Disease Control and Prevention (1994) criteria. Participants who had organic diseases that explained the CF were excluded. A total of 159 participants were asked to complete the QBYY-Q, the fatigue severity scale, and the Chalder fatigue scale. The latter two questionnaires were used to assess convergent validity with the QBYY-Q. Among the 129 CF participants, 70 and 59 had chronic fatigue syndrome and idiopathic chronic fatigue, respectively. Two Korean medical doctors independently assessed participants’ qi, blood, yin, and yang deficiency patterns using QBYY deficiency pattern identification guidelines. Based on the results of a preliminary study of the QBYY-Q, we selected 32 reliable items for symptoms corresponding to each deficiency pattern. The items were used to estimate internal consistency and construct validity. Multinomial logistic regression analysis was performed for scores on each deficiency pattern.

Results

The data were means and standard deviations or numbers of participants and proportions for continuous and categorical variables, respectively. A statistical significance level of P < 0.05 was assumed. The QBYY-Q showed satisfactory internal consistency. Explanatory factor analysis extracted two factors for each deficiency pattern. The percentages of explained variance for qi, blood, yin, and yang deficiency were 45.1, 58.0, 52.2, and 63.4 %, respectively. Each QBYY-Q deficiency score was positively associated with each corresponding deficiency pattern. Qi deficiency was used as a reference category. Odds ratios of blood, yin, and yang deficiency were 10.97, 10.69, and 14.64, respectively.

Conclusion

The QBYY-Q was suitable for estimating the influences of qi, blood, yin, and yang deficiencies in CF.

Trial registration This trial was registered with the Korean Clinical Trial Register (KCT0001199)

Electronic supplementary material

The online version of this article (doi:10.1186/s13020-016-0092-y) contains supplementary material, which is available to authorized users.